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st: statalist-digest V4 #3716


From   statalist-digest <owner-statalist@hsphsun2.harvard.edu>
To   <statalist-digest@hsphsun2.harvard.edu>
Subject   st: statalist-digest V4 #3716
Date   Tue, 2 Mar 2010 02:33:06 -0500

statalist-digest        Tuesday, March 2 2010        Volume 04 : Number 3716



** Send unsubscribe or help commands to majordomo@hsphsun2.harvard.edu  **

The digest contains:

 st: uninstall a command
 Re: st: uninstall a command
 st: RE: RE: re: xtivreg2 - Incomplete computation of first stage regression
 st: RE: controlling display formats in macros
 st: lags with multiply imputed panel data
 st: bootstrap in factor analysis
 st: Re: R for Stata Users
 st: AW: bootstrap in factor analysis
 st: I need help with Extreme Bound Analysis
 st: Tests of overidentifying restrictions after xtivreg2 
 st: using spmap and option "point"
 Re: st: Calculate individual distance from other group members
 Re: st: re: Solving the moving average in the error structure in a  panel data fe
 st: estimating production function
 st: AW: Tests of overidentifying restrictions after xtivreg2 
 st: Competing Risk for repeated event nominal dependent variables
 st: testing a model
 st: Sign of Lambda in heckman
 Re: st: Scandinavian letters in Stata
 st: AW: testing a model
 st: AW: Sign of Lambda in heckman
 st: Ana Timberlake obituary
 Re: st: testing a model
 Re: st: Repeated time values within panel in levpet STATA output
 Re: st: lags with multiply imputed panel data
 RE: st: lags with multiply imputed panel data
 st: Missing data on outcome and sample selection bias
 st: AW: AW: testing a model
 st: Endogenous Regressors Predicted by the Same IV
 re: st: Tests of overidentifying restrictions after xtivreg2
 re: st: re: Solving the moving average in the error structure in a
 re: st: Endogenous Regressors Predicted by the Same IV
 st: RE: Missing data on outcome and sample selection bias
 Re: st: RE: Missing data on outcome and sample selection bias
 Re: st: re: Solving the moving average in the error structure in a
 re: st: re: Solving the moving average in the error structure in a
 st: FAQ reminders
 st: Panel LM Unit Root Test with Heterogenous Structural Breaks
 Re: st: re: Solving the moving average in the error structure in a
 st: Text editor that has automatic table of contents?
 st: Fwd: Saving results in program/loop
 st: RE: Text editor that has automatic table of contents?
 re: st: Fwd: Saving results in program/loop
 st: RE: Text editor that has automatic table of contents?
 Re: st: Endogenous Regressors Predicted by the Same IV
 st: vector with weighted observations question
 st: expected values after xtpcse
 st: RE: I need help with Extreme Bound Analysis
 Re: st: Text editor that has automatic table of contents?
 st: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering
 st: RE: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering
 Re: st: expected values after xtpcse
 Re: st: lags with multiply imputed panel data
 Re: st: lags with multiply imputed panel data
 st: RE: AW: bootstrap in factor analysis
 st: RE: Text editor that has automatic table of contents?
 st: Question on survey data analysis
 st: RE: RE: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering
 Re: st: using spmap and option "point"

----------------------------------------------------------------------

Date: Mon, 1 Mar 2010 03:37:08 -0500
From: Nirina F <fstata@gmail.com>
Subject: st: uninstall a command

Hello,
I installed cmp through
ssc install ghk2, replace
ssc install cmp
Could you please let me know how to uninstall it?
Thank you,
Nirina
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------------------------------

Date: Mon, 1 Mar 2010 03:40:18 -0500
From: Nirina F <fstata@gmail.com>
Subject: Re: st: uninstall a command

never mind Folks, I did -ssc uninstall- and it worked. Thank you

On Mon, Mar 1, 2010 at 3:37 AM, Nirina F <fstata@gmail.com> wrote:
> Hello,
> I installed cmp through
> ssc install ghk2, replace
> ssc install cmp
> Could you please let me know how to uninstall it?
> Thank you,
> Nirina
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>

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------------------------------

Date: Mon, 1 Mar 2010 16:56:15 +0800
From: "Lim Boon Leong" <lboonl@streamyx.com>
Subject: st: RE: RE: re: xtivreg2 - Incomplete computation of first stage regression

Dear Mark, Kit et al.,

After trying out your methods to fix the problem, it really works.  Really
thank you very much for your kind assistance.  Next I am going to check the
problem of misspecification of equation as suggested by Kit.

Best regards,
Lim Boon Leong  


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------------------------------

Date: Sun, 28 Feb 2010 13:22:55 -0600
From: "Richard T. Campbell" <dcamp@uic.edu>
Subject: st: RE: controlling display formats in macros

Many thanks to Kit Baum, Eric Booth and Martin (or is it Maarten?) Weiss who
provided a quick response to my query regarding macros in graph titles. Works
like a charm and I learned a bit more about Stata.



/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/
Richard T. Campbell
Institute for Health Research and Policy
University of Illinois at Chicago, M/C 275
1747 W. Roosevelt Rd.
Chicago, IL  60608
312-413-0480
http://www.ihrp.uic.edu/.
/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/

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------------------------------

Date: Sun, 28 Feb 2010 13:51:53 -0500
From: Daniel Miller <danielpmiller@gmail.com>
Subject: st: lags with multiply imputed panel data

- --001636e1f95a4908b60480ada0fd
Content-Type: text/plain; charset=ISO-8859-1

Hello all ---- I had posted this once already with no replies, and thought I
would give it one more shot:

I am having trouble getting Stata to implement lags (using the L. command)
on my dataset of multiply imputed panel data.

I reshaped the data from wide form to long form in the following way:

gen i =_mi
mim, cat(manip) sortorder(idnum i): xtset idnum wave

where idnum is the unique identifier for respondents and wave is the time
variable (4 time points).

In browse view, the data look like:
*_mj    _mi    i    idnum    wave*
1       1    1    1000001    1
1       2    2    1000001    2
1       3    3    1000001    3
1       4    4    1000001    4
2       1    1    1000001    1
2       2    2    1000001    2
2       3    3    1000001    3
2       4    4    1000001    4
..........................
5       5    5    1000001    4


When I try to use a lagged treatment variable, I get an error message:

e.g.
mim: xtreg fwork l.ratecata1, fe
- -> _mj==1
- -> xtreg fwork l.ratecata1, fe
not sorted
r(5);

Clearly, the data are not sorted properly, but I am unable to find the
proper sort order.

I am able run any lag command on the imputed datasets individually by
sorting like this:
sort idnum wave

but combining the results from each dataset is tedious and am hoping for
some insight on how to fix the problem.

thank you so much in advance,
Daniel Miller
Assistant Professor
Boston University School of Social Work

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- --001636e1f95a4908b60480ada0fd--

------------------------------

Date: Mon, 1 Mar 2010 11:21:02 +1300
From: Thu Phuong Truong <Phuong.Truong@vuw.ac.nz>
Subject: st: bootstrap in factor analysis

Dear Martin and statalister,

Thank so much for getting back to me. I am sorry that I did not make it clear in my previous email. I could do bootstrap for regression. However, I have trouble with factor analysis as I do not know what I should include in the exp_list.

For example
bootstrap exp_list, reps(1000): factor reform_index analyst_index herfindahl5_index ceochair_index brdsize_index brdindp1a ac_index if firmyeartestqualified==1, pcf

What should I include as exp_list in order to test whether the factor loadings are significantly from zero?

Thank so much for your help.

Yours sincerely,

Phuong

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------------------------------

Date: Sun, 28 Feb 2010 09:05:30 -0700
From: Joseph Hilbe <j.m.hilbe@gmail.com>
Subject: st: Re: R for Stata Users

- --000e0cd649643c27940480ab4d75
Content-Type: text/plain; charset=ISO-8859-1

StataListers:

I sent this message on Saturday, but it did not go through. I believe I must
have been using a rich text editor, which Statalist does not accept. I tried
again this morning, but recalled that i have gmail, which is pure text. I am
sending it through gmail in case aol still does not go through. If you get
this twice, my apologies.
- ------

I am not on the Statalist, but do take the Digest, so do not get the
listings until the following day. Most of the time I try to see what has
been discussed, sometimes i just don't have the time. Fortunately I looked
this morning.

Bob Muenchen of the Univ of Tennessee wrote a book a couple of years ago
titled "R for SAS and SPSS users"  The folks at both SPSS and SAS have
seemed to love it, once they realized that the book was aimed to help
SAS/SPSS users who also wanted to learn R. It was not written to convert
anyone from SAS/SPSS to R. Bob is a SAS user and has no intention of
changing.

The statistics editor at Springer contacted me about working with Bob for a
book to be titled "R for Stata Users" He knew that I added R code at the end
of the chapters of my then recently published "Logistic Regression Models"
(May 2009, Chapman & Hall/CRC) which - insofar as it was possible - was
aimed to produce output corresponding to the Stata examples I use throughout
the text. I initially did this to assist members of my classes with
Statistics.com. I teach Logistic Regression and Advanced Logistic
Regression, as well as a couple of other courses for them. Nearly all
"students" are professors who teach statistics courses in some discipline,
or active researchers wanting to update their knowledge of certain area of
statistics. Many -- perhaps even most -- of these students use R, with SAS
as the next most common sofware of preference. Very few come to class as
Stata users. From the feedback I get however, many of these students are so
impressed with what Stata can do that they end up as Stata users after the
class is over. They most definitely end up respecting Stata for its scope of
capabilities and ease of use. I have a 30 page tutorial on Stata as Appendix
A to help these students, and provide references to other places where they
can learn Stata, including the suite of Stata Press books. Man times I have
to tell them that there simply is no corresponding SAS, SPSS, or R function
available for some procedure we are discussing.

It is clear in Logistic Regression Models that Stata has for more modeling
capabilities in this area than is available in R. I have a couple of my
later chapters which have no R examples at the end of chapter, eg the
chapter on exact logistic regression.  But there are areas in which someone
has posted a library of functions to CRAN that is not available in Stata; eg
wavelets. I needed to write a NB2-NB1 hurdle model for a project a week ago.
Stata does not have a command for it, and I or anyone else I know has not
written one, but it is available using the flexmix function in R. This does
not happen much, but it can happen to any of us.

Now - to address the questions raised. I joined the project with Bob because
it is clear from email I get, from students and other profs I relate with,
and from what I see myself, that many - perhaps most - textbooks now being
published use R for examples. R is free and is not a commercial package.
Many university stat departments are now requiring that their students learn
R. And, from what I see being on the editorial boards of 7 journals now,
most examples used in Journals employ R.

What does this mean? Well, as a long time committed Stata user (some 22
years now) it means that if I am going to get the most from textbooks using
R for examples, and if I am to better understand articles using R for
examples, then I want to understand the basics of R.  If I am to better help
my R-using students to understand the Stata code and examples I use in my
books, I should know R so that i can use it to teach them how to understand
Stata and the examples. But there are some models that are not yet available
in Stata, but are available in R.

I didn't write the cover -- but the purpose of the book is to help Stata
users learn enough R to
1) better understand texts and journal articles employing R for examples,
and
2) to better be able to use R for the estimation of statistical procedures
that are currently unavailable in Stata. This includes how to set up
variables/observations, deal with missing values, and so forth.

I can't imagine anyone actually switching from Stata to R, unless they
simply have no money to purchase the software and do not have access to a
university site license. there is nowhere in the book that advocates such a
change. In fact, for portions of the book that I wrote, I compare Stata code
with R code for doing some operation or functions. Mostly Stata is easier  -
but sometimes not.

I myself find it much easier to use Stata than R for most commands and
operations. I too had trouble with the R "if"operator - because there isn't
any. this was difficult for me at first, but there are ways to perform the
operation that end up not so bad at all. However, Stata is more direct.

The foremost area of instruction in "R for Stata Users" is perhaps data
management. This is the area that is most difficult for Stata users trying
to interpret R code that is presented in a text or article. There are two
chapters on graphics and one on basic statistical commands, but nothing
beyond linear regression and ANOVA.

The book is NOT for Stata users who have no reason to learn R. If it were
not for me having so many students who are R users and having to present
materials aimed to teach various statistical methods, and if I did not want
to better understand texts and journal articles that use R, I would have no
reason at all for learning it. Also, I referee more articles than I have
time for, in addition to my AE responsibilities, and find that the majority
of manuscripts I get use R for their examples. In order to do a more
responsible job as referee I felt that I needed to learn R.  But that has no
bearing on what my preferred statistical package is for my own work. It is
clearly Stata - for a host of reasons. But I still find it useful to know R
as well. And that is the point of the book. The book was written for those
wanting to augment Stata, or to better understand sources that use R for
examples. I have found learning R useful at times, you may as well.

Joseph Hilbe

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- --000e0cd649643c27940480ab4d75--

------------------------------

Date: Mon, 1 Mar 2010 14:07:42 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: AW: bootstrap in factor analysis

<> 

Type -ereturn list- after the factor command to see the available returned
results:


*************
webuse bg2, clear
factor bg2cost1-bg2cost6, factors(2) pcf
eret li
*************



HTH
Martin

- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Thu Phuong
Truong
Gesendet: Sonntag, 28. Februar 2010 23:21
An: statalist@hsphsun2.harvard.edu
Betreff: st: bootstrap in factor analysis

Dear Martin and statalister,

Thank so much for getting back to me. I am sorry that I did not make it
clear in my previous email. I could do bootstrap for regression. However, I
have trouble with factor analysis as I do not know what I should include in
the exp_list.

For example
bootstrap exp_list, reps(1000): factor reform_index analyst_index
herfindahl5_index ceochair_index brdsize_index brdindp1a ac_index if
firmyeartestqualified==1, pcf

What should I include as exp_list in order to test whether the factor
loadings are significantly from zero?

Thank so much for your help.

Yours sincerely,

Phuong

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------------------------------

Date: Sun, 28 Feb 2010 21:40:46 -0600
From: Kwame <kwa-me@live.com>
Subject: st: I need help with Extreme Bound Analysis

- --_a1550739-25fb-4388-a931-70162ff4dd94_
Content-Type: text/plain; charset="Windows-1252"
Content-Transfer-Encoding: quoted-printable






Dear Statalist Veterans:


I
am new to Stata but have a project requiring eba (Extreme Bound
Analysis). The equation I am estimating is in the form:


Y =3D a +BiI+BmM+BzZ+u

=20

Y is the dependent variable=20

I is the vector of free variables (one variable in the present)

M is a vector of four variables of interest

Z is a vector of control variables
(ten in this case)


I want Stata to
take tow Z variables in each combination (with the I variable and one M var=
iable) but have been getting syntax
errors as I try. Below are two questions I=92d like you to help me with bas=
ed upon what
I=92ve explained above:=20



What is the correct command to run the
     model for each of the variables(M)of interest?Is it possible to run eb=
a for all the
     four variables of interest with a single command and if so what will i=
t be?
I appreciate any help you can offer me with this.


Kwame
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- --_a1550739-25fb-4388-a931-70162ff4dd94_--

------------------------------

Date: Mon, 1 Mar 2010 20:48:24 +0800
From: "Lim Boon Leong" <lboonl@streamyx.com>
Subject: st: Tests of overidentifying restrictions after xtivreg2 

This is a multipart message in MIME format.

- ------=_NextPart_000_0001_01CAB980.898A11C0
Content-Type: text/plain;
	charset="us-ascii"
Content-Transfer-Encoding: 7bit

Dear Statalisters,

 

I have estimated the following equation by using xtivreg2, gmm function:

 

xtivreg2 lsalary ceodual ........ (ownexr ownex2r ownex3r L.ldiv
L.debt=lrisk ..., fe gmm cluster(id) small ffirst

 

The test results turn out fine.  But when I continue with the xtoverid test
after the above estimation, 

 

xtoverid, cluster(id)

 

the following error message appears:

 

xtoverid error: internal reestimation of eqn differs from original

r(198);

 

I read the help file of xtoverid and it is mentioned that it supports
xtivreg2.  May I know what is the problem and how to fix it?

 

Thank you very much in advance.

 

Best regards,

Lim Boon Leong 

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- ------=_NextPart_000_0001_01CAB980.898A11C0--

------------------------------

Date: Mon, 1 Mar 2010 03:35:47 -0500
From: "Vitorino, Maria Ana" <vitorino@wharton.upenn.edu>
Subject: st: using spmap and option "point"

Dear statalist users,

Is the following possible?

I have 2 files:

*file1 is something like:

region populationsize  id
A            ...                	  1
B            ...              		  2
C           ...               	  3

(I also have a file with the region coordinates so that I can use spmap)

*file 2 is something like:

store_id  xcoord  ycoord
100          ...			...
201           ...		...       
345          ...			...
411           ...		...
544          ...			...



I would like to do a map with the stores superimposed on the map but only for the stores that are located in region B or C (note that I don't have that information on file2, otherwise it would be easy to do), excluding store 345 (irrespective of where it is located).

If I do something like the following, the problem is that all the stores (even the ones that are not located in regions B or C) show up...and I only want the ones located in regions B or C.

spmap populationsize if region=="B" | region=="C" using file1coord, id(id) point(data("file2.dta") xcoord(xcoord) ycoord(ycoord) fcolor(emerald) select(drop if store_id==345))

How can I modify this command line to achieve what I'm looking for?

Any help is appreciated.
Thanks!

Ana


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------------------------------

Date: Mon, 1 Mar 2010 13:31:17 +0100
From: Kartika Sari <kartika.sj@gmail.com>
Subject: Re: st: Calculate individual distance from other group members

- --000e0cd76222fa983d0480bc6c03
Content-Type: text/plain; charset=ISO-8859-1

Dear Austin,

Thanks a lot for your help.
The problem is solved.
I used the joinby command to first create the pair. and then merge with the
distance.

Best regards,
Kartika

2010/2/24 Austin Nichols <austinnichols@gmail.com>

> Kartika Sari <kartika.sj@gmail.com>:
> Like so, then?
>
> clear all
> input gid id ward d1 d2 d3 d4 d5
> 1 1 3 10 4 0 9 7
> 1 2 1 0 6 10 8 5
> 1 3 2 6 0 4 11 3
> 1 4 1 0 6 10 8 5
> 1 5 2 6 0 4 11 3
> 2 1 3 10 4 0 9 7
> 2 2 1 0 6 10 8 5
> 2 3 2 6 0 4 11 3
> end
> qui forv i=1/7 {
> g i`i'=.
> }
> bys gid (id): assert id[1]==1
> bys gid (id): assert id==id[_n-1]+1 if _n>1
> qui forv i=1/7 {
> bys gid (id): replace i`i'=d`=ward[`i']' if ward[`i']<.
> }
> l, noo
>
> See also
> http://www.stata.com/support/faqs/data/members.html
> (though it has some weird editing-induced typos e.g. "We have seen
> that for some problems there is an advantage in using integer
> identifiers which run from 1 and above within each group. If such
> identifiers do not exist, they can be created, as seen in section 5.")
>
> On Tue, Feb 23, 2010 at 4:28 PM, Kartika Sari <kartika.sj@gmail.com>
> wrote:
> > Yes, the assert stop the calculation.
> > I tried not to use assert to see what will happen, and try several
> > combination, but off course, it didn't work.
> >
> > so the variables I have:
> >
> > for each individual: GroupID MemberID (1 to 7) WardID (1 to 74) Ward_1
> > Ward_2 etc Ward_74 that shows distance from ward where the person live to
> > other 73 wards (0 for the ward he live in).
> >
> > But, sometimes member of group are only 2 or 3.
> >
> > Any suggestions?
> >
> > thanks in advanced
> > Kartika
> >
> > 2010/2/23 Martin Weiss <martin.weiss1@gmx.de>
> >
> >>
> >> <>
> >>
> >> " and for the Group, it is not uniform at 5, it is from 1 to
> >> 7."
> >>
> >>
> >> Are the ids within the wards contiguous, i.e. 1,2,3,4? If not, the
> -assert-
> >> line in Austin`s code will stop Stata.
> >>
> >>
> >>
> >>
> >>
> >> HTH
> >> Martin
> >>
> >>
> >> -----Original Message-----
> >> From: owner-statalist@hsphsun2.harvard.edu
> >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Kartika Sari
> >> Sent: Dienstag, 23. Februar 2010 21:46
> >> To: statalist@hsphsun2.harvard.edu
> >> Subject: Re: st: Calculate individual distance from other group members
> >>
> >> Austin,
> >> Thanks for your reply. Yes, i would like to have something like that.
> >>
> >> But, its turn out the actual data is more complicated than the
> hypothetical
> >> I made before.
> >> I have 74 wards. and for the Group, it is not uniform at 5, it is from 1
> to
> >> 7.
> >>
> >> So?
> >>
> >> Best regards,
> >> Kartika
> >>
> >>
> >> 2010/2/23 Austin Nichols <austinnichols@gmail.com>
> >>
> >> > Kartika Sari <kartika.sj@gmail.com>:
> >> > Like so?
> >> >
> >> > clear all
> >> > input gid id ward d1 d2 d3 d4 d5
> >> > 1 1 3 10 4 0 9 7
> >> > 1 2 1 0 6 10 8 5
> >> > 1 3 2 6 0 4 11 3
> >> > 1 4 1 0 6 10 8 5
> >> > 1 5 2 6 0 4 11 3
> >> > end
> >> > forv i=1/5 {
> >> > bys gid (id): assert id[`i']==`i'
> >> > bys gid (id): g i`i'=d`=ward[`i']'
> >> > }
> >> > l, noo
> >> >
> >> > On Tue, Feb 23, 2010 at 11:22 AM, Kartika Sari <kartika.sj@gmail.com>
> >> > wrote:
> >> > > Dear All,
> >> > >
> >> > > In my data, I have  a distance matrix of  wards for each individual.
> I
> >> > also
> >> > > know in which ward they live. The problem is i want to calculate
> ward
> >> > > distance from each individual to each of other members in a group.
> Say
> >> > there
> >> > > are 5 people in a group, so I need to calculate distance for 4
> others
> >> for
> >> > > each person. I am wondering whether there is any syntax for this.
> >> > >
> >> > > The structure of data is something like this:
> >> > >
> >> > > group_id individual_id ward dtoward1 dtoward2 dtoward3 dtoward4
> >> dtoward5
> >> > > distance1? distance2? distance3? distance4?
> >> > > 1 1 3 10 4 0 9 7
> >> > > 1 2 1 0 6 10 8 5
> >> > > 1 3 2 6 0 4 11 3
> >> > > 1 4 1 0 6 10 8 5
> >> > > 1 5 2 6 0 4 11 3
> >> > >
> >> > > Thank you very much in advanced.
> >> > >
> >> > > Best regards,
> >> > > Kartika
> >> > >
>
> *
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>

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- --000e0cd76222fa983d0480bc6c03--

------------------------------

Date: Mon, 1 Mar 2010 12:50:13 +0100
From: Carolina Lennon <carolina.lennon@gmail.com>
Subject: Re: st: re: Solving the moving average in the error structure in a  panel data fe

- --00504502cffe279ad30480bbda82
Content-Type: text/plain; charset=ISO-8859-1

Thank you for the your response!  as usual, it was very fast!

I have another question related to my previous email (see below).

You suggested to use "xtivreg2, fe with options  robust bw(5)"  in order to
obtain statistics robust to heteroskedasticity and to the autocorrelation
generated by the 4 lags in my overlaping sample (of data calculated using 5
years). I am currently using this method!!!

But now, I would like to correct the bias in the "estimates" (the
coefficients) generated by the MA error structure. I was wondering If I can
use xtslg. Though, xtslg has not the option bw(5) and I am not sure how to
set up the within panel correlations. In particular, I am not very sure how
to set up the  corr(corr) and  rhotype(calc) options. If you can advise me
in this respect I would really appreciate it!

Many thanks
Carolina



2010/2/22 Kit Baum <baum@bc.edu>

> <>
> Carolina wrote
>
> I am working with a fixed effect model.
> My dependent variable is the sd of the growth rate of countries GDPs,
> calculated over a period of 5 years. The explanatory variables are in
> standard deviation as well and they are calculated over the same period of
> years.
>
> I would like to use the overlapping sample ideally using fe estimation,
> though for that I would need to correct for the outocorrelation generated
> by
> the moving average!
>
> That said, do you know if STATA has an option to correct this problem for
> panel data! Ideally for fixed effect estimations?
> If there were not, it is possible to program a new tipe of VCE matrix
> (adjusting by the number of data overlaps)?
>
>
> ssc desc xtivreg2
> ssc inst ivreg2
> ssc inst xtivreg2
> ssc inst ranktest
>
> Use xtivreg2, fe with options  robust bw(5)  to take care of the MA(4) in
> your overlapping data.
>
> Kit Baum   |   Boston College Economics & DIW Berlin   |
> http://ideas.repec.org/e/pba1.html
>                              An Introduction to Stata Programming  |
> http://www.stata-press.com/books/isp.html
>   An Introduction to Modern Econometrics Using Stata  |
> http://www.stata-press.com/books/imeus.html
>
>
> *
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>



- -- 
Carolina Lennon

Mobile in Austria:  (43) 06 76 59 24 553
Office at Wiiw in Vienna:  (43) 01 533 66 10 86
Institute website: http://www.wiiw.ac.at
Personal website: http://carolina.lennon.research.googlepages.com/

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- --00504502cffe279ad30480bbda82--

------------------------------

Date: Mon, 1 Mar 2010 12:57:30 +0100
From: "Martinez San Roman, Valeriano" <valeriano.martinez@unican.es>
Subject: st: estimating production function

Dear Stata users,

I hope you can help me. I am trying to estimate a cobb-douglas
production function (Y=X1^a*X2^b*X3^c*....) using panel data with fixed
effects.

I am using the log of the production function as my functional form,
that is, Ln(Y) = aLn(X1) + bLn(X2) + cLn(X3)+....

And I have to assume that we have constant returns to scale, in other
words, the sum of the exponentials must be equal to 1 (a+b+c+...=1)

Is there a command to restrict the sum of exponentials to be equal to 1.
How can I do it?

Thank you very much,
Valeriano



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------------------------------

Date: Mon, 1 Mar 2010 14:13:24 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: AW: Tests of overidentifying restrictions after xtivreg2 

<> 

Search the archive, and you get, for instance,
http://www.stata.com/statalist/archive/2007-07/msg00979.html






HTH
Martin


- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Lim Boon Leong
Gesendet: Montag, 1. M�rz 2010 13:48
An: statalist@hsphsun2.harvard.edu
Betreff: st: Tests of overidentifying restrictions after xtivreg2 

Dear Statalisters,

 

I have estimated the following equation by using xtivreg2, gmm function:

 

xtivreg2 lsalary ceodual ........ (ownexr ownex2r ownex3r L.ldiv
L.debt=lrisk ..., fe gmm cluster(id) small ffirst

 

The test results turn out fine.  But when I continue with the xtoverid test
after the above estimation, 

 

xtoverid, cluster(id)

 

the following error message appears:

 

xtoverid error: internal reestimation of eqn differs from original

r(198);

 

I read the help file of xtoverid and it is mentioned that it supports
xtivreg2.  May I know what is the problem and how to fix it?

 

Thank you very much in advance.

 

Best regards,

Lim Boon Leong 

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------------------------------

Date: Sun, 28 Feb 2010 11:55:44 -0500
From: "David A. Cort" <dcort@soc.umass.edu>
Subject: st: Competing Risk for repeated event nominal dependent variables

Dear Listserv,

I am attempting to fit discrete-time event history model where the 
outcome is nominal and can be repeated over time. The social process is 
residential mobility. Instead of wanting to know the risk of moving into 
a community or neighborhood (Allison-type model), I'm interested in the 
risk of moving into a specific type of neighborhood. The dependent 
variable therefore has multiple categories (4 to be specific) for 
neighborhood type and time is discretized (into months). Any help 
concerning how STATA 10 can handle this type of setup would be very helpful.

David

- -- 
David A. Cort
Assistant Professor
Dept. of Sociology
University of Massachusetts, Amherst
702 Thompson Hall
200 Hicks Way
Amherst, MA 01003-9277
Phone: 413-545-1041
E-mail: dcort@soc.umass.edu
Web: www.people.umass.edu/dcort

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------------------------------

Date: Mon, 1 Mar 2010 14:23:25 +0100
From: luc paugam <lukepaugam@gmail.com>
Subject: st: testing a model

- --00032555af2e6924370480bd2733
Content-Type: text/plain; charset=ISO-8859-1

Hello everyone,

I am a new user of stata, and I struggle with this particular issue:

I hope I will be clear enough.
I would like to test the accuracy of my model in the following manner:

Estimate my regression with (*N-1*) observations, and with the coefficients
obtained, predict the "*y_hat_i*" of the observation "*i*" I didn't use to
estimate the coefficients.
I would like to do that *N* times, in order to have *N* "*y_hat_i*" (*i=1,
... ,N*).

Than I could compare the "*y_hat_i*" with the real "*y*", and test the
accuracy of my model (mean errors, median error, standard deviation etc.)

I appreciate your time,

Luke

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- --00032555af2e6924370480bd2733--

------------------------------

Date: Mon, 1 Mar 2010 14:26:34 +0100
From: "Sascha Steffen" <steffen@bank.bwl.uni-mannheim.de>
Subject: st: Sign of Lambda in heckman

This is a multi-part message in MIME format.

- ------=_NextPart_000_0001_01CAB94B.31B4AAD0
Content-Type: text/plain;
	charset="us-ascii"
Content-Transfer-Encoding: 7bit

Dear All,

I was wondering about an economic interpretation of the sign of the lambda
in a heckman selection model. For example, I am interested in factors
reducing default rates of firms. I only observe the performance of the loan
once the loan is approved. I use a selection model to account for this. My
lambda from the heckman model turns out to be significant and negative. What
is the interpretation? In what direction is the bias? Can I interpret the
negative sign, that information has been used to screen and filter out bad
applicants? What do you think?

Best wishes,
Sascha

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- ------=_NextPart_000_0001_01CAB94B.31B4AAD0--

------------------------------

Date: Mon, 1 Mar 2010 14:43:30 +0100
From: Johan Hellstrom <johan.hellstrom@pol.umu.se>
Subject: Re: st: Scandinavian letters in Stata

Hi Roland,

I newer had any problems with the Scandinavian letters in Stata.

You might want to consider using an alternative way of importing the data into Stata, e.g. using StatTransfer?

Best,
Johan


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------------------------------

Date: Mon, 1 Mar 2010 14:44:30 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: AW: testing a model

<> 

Getting the coefficients is easy enough via a judicious choice for the vce:


*************
sysuse auto, clear
regress price mpg, vce(jackknife, saving(myfile, replace))
u myfile, clear
l
*************



HTH
Martin


- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von luc paugam
Gesendet: Montag, 1. M�rz 2010 14:23
An: statalist@hsphsun2.harvard.edu
Betreff: st: testing a model

Hello everyone,

I am a new user of stata, and I struggle with this particular issue:

I hope I will be clear enough.
I would like to test the accuracy of my model in the following manner:

Estimate my regression with (*N-1*) observations, and with the coefficients
obtained, predict the "*y_hat_i*" of the observation "*i*" I didn't use to
estimate the coefficients.
I would like to do that *N* times, in order to have *N* "*y_hat_i*" (*i=1,
... ,N*).

Than I could compare the "*y_hat_i*" with the real "*y*", and test the
accuracy of my model (mean errors, median error, standard deviation etc.)

I appreciate your time,

Luke

*
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*   http://www.ats.ucla.edu/stat/stata/


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------------------------------

Date: Mon, 1 Mar 2010 14:53:27 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: AW: Sign of Lambda in heckman

<> 

As [R], p. 651 says: lambda is the product of rho and sigma. If all you are
interested in is the sign, then sigma is irrelevant, since it will always be
positive, being a standard deviation. So you are really asking for
information about rho: I would check the references at the beginning of the
"Methods and formulas" for more insights about its meaning.





HTH
Martin


- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Sascha Steffen
Gesendet: Montag, 1. M�rz 2010 14:27
An: statalist@hsphsun2.harvard.edu
Betreff: st: Sign of Lambda in heckman

Dear All,

I was wondering about an economic interpretation of the sign of the lambda
in a heckman selection model. For example, I am interested in factors
reducing default rates of firms. I only observe the performance of the loan
once the loan is approved. I use a selection model to account for this. My
lambda from the heckman model turns out to be significant and negative. What
is the interpretation? In what direction is the bias? Can I interpret the
negative sign, that information has been used to screen and filter out bad
applicants? What do you think?

Best wishes,
Sascha

*
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*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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------------------------------

Date: Mon, 1 Mar 2010 14:20:06 +0000
From: Ronan Conroy <rconroy@rcsi.ie>
Subject: st: Ana Timberlake obituary

There is a moving tributary to Ana Timberlake, founder of Timberlake  
Consultants, the UK distributors of Stata, in the Guardian. It is a  
measure of the esteem and affection in which she was held by so many  
people that her obituary appeared in a national newspaper.

One of her own pieces of research was the re-analysis of the results  
of Robert Borkenstein's 1964 Grand Rapids study, upon which the  
British breathalyser test had been based in the mid-1960s. The  
original data had not been statistically adjusted and earlier analysis  
had suggested that driving improved with the intake of a small amount  
of alcohol. However, after Ana had standardised the data (for weather,  
vehicle age, driving experience, and so on), it became clear (much to  
the chagrin of the brewers) that alcohol intake did indeed make  
driving capability progressively worse. [description from the Guardian  
piece}

Those of us who met her will remember her fondly, and I am sure that  
our thoughts are with her family at this time.

http://www.guardian.co.uk/theguardian/2010/feb/28/ana-timberlake-obituary

Ronan Conroy
=================================

rconroy@rcsi.ie
Royal College of Surgeons in Ireland
Epidemiology Department,
Beaux Lane House, Dublin 2, Ireland
+353 (0)1 402 2431
+353 (0)87 799 97 95
+353 (0)1 402 2764 (Fax - remember them?)
http://rcsi.academia.edu/RonanConroy

P    Before printing, think about the environment




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------------------------------

Date: Mon, 01 Mar 2010 09:29:15 -0500
From: Richard Goldstein <richgold@ix.netcom.com>
Subject: Re: st: testing a model

have you looked at the -jackknife- command?

Rich

luc paugam wrote:
> Hello everyone,
> 
> I am a new user of stata, and I struggle with this particular issue:
> 
> I hope I will be clear enough.
> I would like to test the accuracy of my model in the following manner:
> 
> Estimate my regression with (*N-1*) observations, and with the coefficients
> obtained, predict the "*y_hat_i*" of the observation "*i*" I didn't use to
> estimate the coefficients.
> I would like to do that *N* times, in order to have *N* "*y_hat_i*" (*i=1,
> ... ,N*).
> 
> Than I could compare the "*y_hat_i*" with the real "*y*", and test the
> accuracy of my model (mean errors, median error, standard deviation etc.)
> 
> I appreciate your time,
> 
> Luke
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------------------------------

Date: Mon, 1 Mar 2010 08:27:13 -0600 (CST)
From: "Brian P. Poi" <bpoi@stata.com>
Subject: Re: st: Repeated time values within panel in levpet STATA output

On Sun, 28 Feb 2010, Worku Gebeyehu wrote:

> Dear Sir/Madam,

> I am a PhD student doing my research on TFP of a panel of firms for the 
> period 1996 to 2007 and the total number of observations are 8395. I 
> have been trying to excute the following levpet command. levpet lny , 
> free(lnl2 lnirm lnlrm) proxy (lnpower) capital (lnk) revenue justid grid 
> i (eid) t (yr) reps (50)
>
> However, I have been facing a problem of 'repeated time values within 
> panel'. I have not faced a similar problem while estimating the same 
> using FE, RE, OP, etc. I also tried to check the existence of 
> dublications of years or firm idenity numbers using the stata 'dublicate 
> report' command, I got a report of 'surplus=0'. Using set tr on, I found 
> the following report. Because I am unable to understand what it means 
> due to lack of knowldge in programming, I sent you with all the junk. I 
> am sorry for that. I am stuck and strongly need your support.
>

If Worku would send the dataset directly to me (bpoi@stata.com), I'd be 
happy to look into the cause of this problem.

   -- Brian Poi   (coauthor of -levpet-)
   -- bpoi@stata.com
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------------------------------

Date: Mon, 1 Mar 2010 15:50:37 +0100
From: Johan Hellstrom <johan.hellstrom@pol.umu.se>
Subject: Re: st: lags with multiply imputed panel data

If the L. prefix does not work, you can see if creating your lagged treatment variable manually will help:

bysort idnum (wave): gen lag_ratecata1=ratecata1[_n-1]

Best,
Johan


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------------------------------

Date: Mon, 1 Mar 2010 14:57:06 -0000
From: "Nick Cox" <n.j.cox@durham.ac.uk>
Subject: RE: st: lags with multiply imputed panel data

If L. "does not work", whatever that means precisely, then what this
yields is a beast of unpredictable shape. 

Better to set the time variable to something appropriate, and let any
missings in those terms be explicit. 

Nick 
n.j.cox@durham.ac.uk 

Johan Hellstrom

If the L. prefix does not work, you can see if creating your lagged
treatment variable manually will help:

bysort idnum (wave): gen lag_ratecata1=ratecata1[_n-1]


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------------------------------

Date: Mon, 1 Mar 2010 07:03:23 -0800 (PST)
From: Rosie Chen <jiarongchen2002@yahoo.com>
Subject: st: Missing data on outcome and sample selection bias

Carlo, thanks for your response. My question is not related to right censoring or independent variables' missing cases. It is the fact that respondents did not answer the question for the outcome variable. We can't impute outcome values, so that's why we often have to delete cases that have missing values on the dependent variable. But there is a potential sample selection bias. 

So dear all,  here are my several questions regarding a multilevel analysis with missing values on the outcome variable:

1)     Do we often compare the deleted cases with the
final raw sample without missing data imputation or with the final
sample with missing cases imputed? 
(2) To what extent do t-tests can be useful for determining sample
selection bias? What criterion do we use? Do the significant t tests on
all predictors indicate such a problem or half of the tests being
significant indicates the problem?
(3)     If t-test is not a very good tool to assess the problem, should we use Heckman method? Can we use Heckman test to detect and remedy the possible sample selection bias problem with a dependent variable in Stata? I learned that there is a Heckman and a GLLMM syntax in Stata, but I am
not sure if it can incorporate all three features (multilevel data structure,
multiple-imputed data, and complex survey design) into consideration.

Your advice would be appreciated very much,

Rosie



- ----- Original Message ----
From: Carlo Lazzaro <carlo.lazzaro@tin.it>
To: statalist@hsphsun2.harvard.edu
Cc: Rosie Chen <jiarongchen2002@yahoo.com>
Sent: Mon, March 1, 2010 1:58:39 AM
Subject: R: Missing data analysis



Dear Rosie,
I am not clear about what you mean with "we have to to delete cases that
have missing values", since this is not the standard practice.

If you mean (right)censored observations, they can be addressed in Stata via
Survival Analysis suite (please, see -stset- and related stuff in Stata
9.2/SE).

For more details on dealing with missing observations, especially when
they're variables rather than outcomes, you might want to take a look at:

Little RJA, Rubin DB. Statistical analysis with missing data. Second
Edition. Hoboken, NJ: Wiley, 2002.

HTH and Kind Regards,

Carlo 

- -----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Rosie Chen
Inviato: domenica 28 febbraio 2010 21.31
A: statalist@hsphsun2.harvard.edu
Oggetto: st: Missing data analysis

Hi, dear listserv members,

   I have a question that is not specifically related to Stata, but would
like to have a try in here: 

   In most studies, we have to delete cases that have missing values on the
outcome variable. The issue is whether the deleted cases are significantly
different from the final sample we use, because of the potential sample
selection bias problem.  My question is: do we often compare the deleted
cases with the final raw sample without missing data imputation or with the
final sample with missing cases imputed? Any suggestions are appreciated
very much,

  Rosie



      
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------------------------------

Date: Mon, 1 Mar 2010 16:25:09 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: AW: AW: testing a model

<> 

And here is how you would obtain "yhats" and errors. Note I am giving
technical details, not, in any way, shape or form endorsing your approach:



*************
sysuse auto, clear

tempfile myfile
regress price mpg, vce(jackknife,  /* 
*/ saving(`myfile', replace))

merge 1:1 _n using `myfile', /* 
*/ norep nogen

gen yhat=_b[_cons]+_b[mpg]*mpg
gen error=price-yhat
*************



HTH
Martin


- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Martin Weiss
Gesendet: Montag, 1. M�rz 2010 14:45
An: statalist@hsphsun2.harvard.edu
Betreff: st: AW: testing a model


<> 

Getting the coefficients is easy enough via a judicious choice for the vce:


*************
sysuse auto, clear
regress price mpg, vce(jackknife, saving(myfile, replace))
u myfile, clear
l
*************



HTH
Martin


- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von luc paugam
Gesendet: Montag, 1. M�rz 2010 14:23
An: statalist@hsphsun2.harvard.edu
Betreff: st: testing a model

Hello everyone,

I am a new user of stata, and I struggle with this particular issue:

I hope I will be clear enough.
I would like to test the accuracy of my model in the following manner:

Estimate my regression with (*N-1*) observations, and with the coefficients
obtained, predict the "*y_hat_i*" of the observation "*i*" I didn't use to
estimate the coefficients.
I would like to do that *N* times, in order to have *N* "*y_hat_i*" (*i=1,
... ,N*).

Than I could compare the "*y_hat_i*" with the real "*y*", and test the
accuracy of my model (mean errors, median error, standard deviation etc.)

I appreciate your time,

Luke

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------------------------------

Date: Mon, 1 Mar 2010 07:48:03 -0800 (PST)
From: Lloyd Dumont <lloyddumont@yahoo.com>
Subject: st: Endogenous Regressors Predicted by the Same IV

Hello, Statalist.

Iâ??m pretty sure that what weâ??re trying to do is mathematically estimable under certain assumptions.  So, we are trying to figure out the syntax for the estimating procedure.  And, then weâ??d like to clarify the assumptions that have to hold for us to accept the estimates.

We are ultimately trying to estimate a dep var we will call Y_dep.  Y_dep is being predicted by X_1, X_2, â?¦X_10.  But, X_1, X_2, and X_3 are all endogenous.  We believe they can all be predicted by the same instrumental variable, Z_1.  And, furthermore, we are willing to accept that Z_1 has no direct effect on Y_dep beyond its effects through X_1, X_2, and X_3.

Just to make this all a tad more complicated, Y_dep is actually binary, and, this is all being done with survey data.

A simple approach usingâ?¦

svy linearized : ivprobit â?¦

seems to preclude our removing certain regressors from the first stage, which we think MAY be part of the required solution to the problem.  If we are wrong about that, then there may be a way to use ivprobit?  But, we're open to ANY suggestions.

Thank you for your help.  Lloyd.


      


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------------------------------

Date: Mon, 1 Mar 2010 10:56:25 -0500
From: Kit Baum <baum@bc.edu>
Subject: re: st: Tests of overidentifying restrictions after xtivreg2

<>
I have estimated the following equation by using xtivreg2, gmm function:

 

xtivreg2 lsalary ceodual ........ (ownexr ownex2r ownex3r L.ldiv
L.debt=lrisk ..., fe gmm cluster(id) small ffirst

 

The test results turn out fine.  But when I continue with the xtoverid test
after the above estimation, 

 

xtoverid, cluster(id)

 

the following error message appears:

 

xtoverid error: internal reestimation of eqn differs from original

r(198);

 

I read the help file of xtoverid and it is mentioned that it supports
xtivreg2.  May I know what is the problem and how to fix it?



This appears to be a bug in xtoverid, and the authors of that routine have been notified. However there is no reason to use xtoverid (from SSC) in this case. The xtivreg2 output, with GMM option invoked, gives you a Hansen J statistic. If xtoverid worked properly, it would give you the same J statistic. The only need for xtoverid is if you had used official xtivreg rather than user-written xtivreg2.

Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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------------------------------

Date: Mon, 1 Mar 2010 10:58:52 -0500
From: Kit Baum <baum@bc.edu>
Subject: re: st: re: Solving the moving average in the error structure in a

<>
Carolina said

But now, I would like to correct the bias in the "estimates" (the
coefficients) generated by the MA error structure. I was wondering If I can
use xtslg. Though, xtslg has not the option bw(5) and I am not sure how to
set up the within panel correlations. In particular, I am not very sure how
to set up the  corr(corr) and  rhotype(calc) options. If you can advise me
in this respect I would really appreciate it!


There is no reason for a MA error structure to induce bias in the OLS coefficients. Departures from IID errors do not generally cause bias or inconsistency in the point estimates. They mess up the VCE. The use of GLS techniques is motivated by the desire to get unbiased point and interval estimates.

I'm not sure what 'xtslg' is.

Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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------------------------------

Date: Mon, 1 Mar 2010 11:01:31 -0500
From: Kit Baum <baum@bc.edu>
Subject: re: st: Endogenous Regressors Predicted by the Same IV

<>
Iâ??m pretty sure that what weâ??re trying to do is mathematically estimable under certain assumptions.  So, we are trying to figure out the syntax for the estimating procedure.  And, then weâ??d like to clarify the assumptions that have to hold for us to accept the estimates.

We are ultimately trying to estimate a dep var we will call Y_dep.  Y_dep is being predicted by X_1, X_2, â?¦X_10.  But, X_1, X_2, and X_3 are all endogenous.  We believe they can all be predicted by the same instrumental variable, Z_1.  And, furthermore, we are willing to accept that Z_1 has no direct effect on Y_dep beyond its effects through X_1, X_2, and X_3.


No can do. This is a textbook case of under(un)identification. You need at least three Z variables to identify the equation, whether or not the estimation technique is OLS, probit, etc.

Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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------------------------------

Date: Mon, 1 Mar 2010 08:12:09 -0800
From: "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
Subject: st: RE: Missing data on outcome and sample selection bias

I don't understand why you can't impute outcome variables.  ICE will do it.  A recent paper by van Hippel notes that a reasonable approach is to impute all the missing values but then delete the cases with missing y-values.   His simulations were for normal variables, but I wouldn't be surprised to see they held for categorical ones.  
Deleting cases without y values is often very dangerous.  I'd use ICE and try it both ways.   Note that ICE will impute categorical values.  

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Rosie Chen
Sent: Monday, March 01, 2010 7:03 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: Missing data on outcome and sample selection bias

Carlo, thanks for your response. My question is not related to right censoring or independent variables' missing cases. It is the fact that respondents did not answer the question for the outcome variable. We can't impute outcome values, so that's why we often have to delete cases that have missing values on the dependent variable. But there is a potential sample selection bias. 

So dear all,  here are my several questions regarding a multilevel analysis with missing values on the outcome variable:

1)     Do we often compare the deleted cases with the
final raw sample without missing data imputation or with the final
sample with missing cases imputed? 
(2) To what extent do t-tests can be useful for determining sample
selection bias? What criterion do we use? Do the significant t tests on
all predictors indicate such a problem or half of the tests being
significant indicates the problem?
(3)     If t-test is not a very good tool to assess the problem, should we use Heckman method? Can we use Heckman test to detect and remedy the possible sample selection bias problem with a dependent variable in Stata? I learned that there is a Heckman and a GLLMM syntax in Stata, but I am
not sure if it can incorporate all three features (multilevel data structure,
multiple-imputed data, and complex survey design) into consideration.

Your advice would be appreciated very much,

Rosie



- ----- Original Message ----
From: Carlo Lazzaro <carlo.lazzaro@tin.it>
To: statalist@hsphsun2.harvard.edu
Cc: Rosie Chen <jiarongchen2002@yahoo.com>
Sent: Mon, March 1, 2010 1:58:39 AM
Subject: R: Missing data analysis



Dear Rosie,
I am not clear about what you mean with "we have to to delete cases that
have missing values", since this is not the standard practice.

If you mean (right)censored observations, they can be addressed in Stata via
Survival Analysis suite (please, see -stset- and related stuff in Stata
9.2/SE).

For more details on dealing with missing observations, especially when
they're variables rather than outcomes, you might want to take a look at:

Little RJA, Rubin DB. Statistical analysis with missing data. Second
Edition. Hoboken, NJ: Wiley, 2002.

HTH and Kind Regards,

Carlo 

- -----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Rosie Chen
Inviato: domenica 28 febbraio 2010 21.31
A: statalist@hsphsun2.harvard.edu
Oggetto: st: Missing data analysis

Hi, dear listserv members,

   I have a question that is not specifically related to Stata, but would
like to have a try in here: 

   In most studies, we have to delete cases that have missing values on the
outcome variable. The issue is whether the deleted cases are significantly
different from the final sample we use, because of the potential sample
selection bias problem.  My question is: do we often compare the deleted
cases with the final raw sample without missing data imputation or with the
final sample with missing cases imputed? Any suggestions are appreciated
very much,

  Rosie



      
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------------------------------

Date: Mon, 1 Mar 2010 08:32:22 -0800 (PST)
From: Rosie Chen <jiarongchen2002@yahoo.com>
Subject: Re: st: RE: Missing data on outcome and sample selection bias

Thanks, Tony. Let me see if I understand you correctly. Did you mean that, by keeping cases that have missing values on the y variable in the imputation process, we should be able to reduce or remove the possible sample selection bias issue because the imputed x variables' values are based on those cases also? I haven't seen anywhere that this is a standard way to do to address the possible sample selection issue, but please correct me if I am wrong. 


To keep this discussion thread going, I am posting my questions again. Thanks for every input and advice!  -- Rosie

Dear all,  here are my several questions regarding a multilevel analysis with missing values on the outcome variable:

1)     Do we often compare the deleted cases with the
final raw sample without missing data imputation or with the final
sample with missing cases imputed? 
(2) To what extent do t-tests can be useful for determining sample
selection bias? What criterion do we use? Do the significant t tests on
all predictors indicate such a problem or half of the tests being
significant indicates the problem?
(3) 
  If t-test is not a very good tool to assess the problem, should we
use Heckman method? 
Can we use Heckman test to detect and remedy the
possible sample selection bias problem with a dependent variable in
Stata? 
I learned that there is a Heckman and a GLLMM syntax in Stata,
but I am not sure if it can incorporate all three features (multilevel data structure,
multiple-imputed data, and complex survey design) into consideration.


- ----- Original Message ----
From: "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Sent: Mon, March 1, 2010 11:12:09 AM
Subject: st: RE: Missing data on outcome and sample selection bias

I don't understand why you can't impute outcome variables.  ICE will do it.  A recent paper by van Hippel notes that a reasonable approach is to impute all the missing values but then delete the cases with missing y-values.   His simulations were for normal variables, but I wouldn't be surprised to see they held for categorical ones.  
Deleting cases without y values is often very dangerous.  I'd use ICE and try it both ways.   Note that ICE will impute categorical values.  

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Rosie Chen
Sent: Monday, March 01, 2010 7:03 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: Missing data on outcome and sample selection bias

Carlo, thanks for your response. My question is not related to right censoring or independent variables' missing cases. It is the fact that respondents did not answer the question for the outcome variable. We can't impute outcome values, so that's why we often have to delete cases that have missing values on the dependent variable. But there is a potential sample selection bias. 

So dear all,  here are my several questions regarding a multilevel analysis with missing values on the outcome variable:

1)     Do we often compare the deleted cases with the
final raw sample without missing data imputation or with the final
sample with missing cases imputed? 
(2) To what extent do t-tests can be useful for determining sample
selection bias? What criterion do we use? Do the significant t tests on
all predictors indicate such a problem or half of the tests being
significant indicates the problem?
(3)     If t-test is not a very good tool to assess the problem, should we use Heckman method? Can we use Heckman test to detect and remedy the possible sample selection bias problem with a dependent variable in Stata? I learned that there is a Heckman and a GLLMM syntax in Stata, but I am
not sure if it can incorporate all three features (multilevel data structure,
multiple-imputed data, and complex survey design) into consideration.

Your advice would be appreciated very much,

Rosie



- ----- Original Message ----
From: Carlo Lazzaro <carlo.lazzaro@tin.it>
To: statalist@hsphsun2.harvard.edu
Cc: Rosie Chen <jiarongchen2002@yahoo.com>
Sent: Mon, March 1, 2010 1:58:39 AM
Subject: R: Missing data analysis



Dear Rosie,
I am not clear about what you mean with "we have to to delete cases that
have missing values", since this is not the standard practice.

If you mean (right)censored observations, they can be addressed in Stata via
Survival Analysis suite (please, see -stset- and related stuff in Stata
9.2/SE).

For more details on dealing with missing observations, especially when
they're variables rather than outcomes, you might want to take a look at:

Little RJA, Rubin DB. Statistical analysis with missing data. Second
Edition. Hoboken, NJ: Wiley, 2002.

HTH and Kind Regards,

Carlo 

- -----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Rosie Chen
Inviato: domenica 28 febbraio 2010 21.31
A: statalist@hsphsun2.harvard.edu
Oggetto: st: Missing data analysis

Hi, dear listserv members,

   I have a question that is not specifically related to Stata, but would
like to have a try in here: 

   In most studies, we have to delete cases that have missing values on the
outcome variable. The issue is whether the deleted cases are significantly
different from the final sample we use, because of the potential sample
selection bias problem.  My question is: do we often compare the deleted
cases with the final raw sample without missing data imputation or with the
final sample with missing cases imputed? Any suggestions are appreciated
very much,

  Rosie



      
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*   http://www.ats.ucla.edu/stat/stata/


      
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------------------------------

Date: Mon, 1 Mar 2010 17:46:53 +0100
From: Carolina Lennon <carolina.lennon@gmail.com>
Subject: Re: st: re: Solving the moving average in the error structure in a

- --001485e9ab560ec0ae0480bfff05
Content-Type: text/plain; charset=ISO-8859-1

Many thanks Kit,

Sorry, I made a spelling mistake in the previous email, I should have said
xtgls instead of xtslg.

Again many thanks for you answer.

I know that the following question is a little out of scope (since it does
not relate to the stata commands), but just in case it is easy for you to
reply...Do you  know where I can find a reference justifying "that there is
no reason for a MA error structure to induce bias in the OLS coefficients"?
It would of great help. Indeed, some referees did not like my overlapping
regressions because of the bias cused by the MA errors in the point
estimates.  (My  regressions were of the type: xtreg, fe cluster) Therefore,
if I can justify it would be just perfect.

Many thanks again
Carolina




2010/3/1 Kit Baum <baum@bc.edu>

> <>
> Carolina said
>
> But now, I would like to correct the bias in the "estimates" (the
> coefficients) generated by the MA error structure. I was wondering If I can
> use xtslg. Though, xtslg has not the option bw(5) and I am not sure how to
> set up the within panel correlations. In particular, I am not very sure how
> to set up the  corr(corr) and  rhotype(calc) options. If you can advise me
> in this respect I would really appreciate it!
>
>
> There is no reason for a MA error structure to induce bias in the OLS
> coefficients. Departures from IID errors do not generally cause bias or
> inconsistency in the point estimates. They mess up the VCE. The use of GLS
> techniques is motivated by the desire to get unbiased point and interval
> estimates.
>
> I'm not sure what 'xtslg' is.
>
> Kit Baum   |   Boston College Economics & DIW Berlin   |
> http://ideas.repec.org/e/pba1.html
>                              An Introduction to Stata Programming  |
> http://www.stata-press.com/books/isp.html
>   An Introduction to Modern Econometrics Using Stata  |
> http://www.stata-press.com/books/imeus.html
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



- -- 
Carolina Lennon

Mobile in Austria:  (43) 06 76 59 24 553
Office at Wiiw in Vienna:  (43) 01 533 66 10 86
Institute website: http://www.wiiw.ac.at
Personal website: http://carolina.lennon.research.googlepages.com/

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- --001485e9ab560ec0ae0480bfff05--

------------------------------

Date: Mon, 1 Mar 2010 12:13:15 -0500
From: Christopher F Baum <baum@bc.edu>
Subject: re: st: re: Solving the moving average in the error structure in a

<>
Carolina said

I know that the following question is a little out of scope (since it  
does not relate to the stata commands), but just in case it is easy  
for you to reply...Do you know where I can find a reference justifying  
"that there is no reason for a MA error structure to induce bias in  
the OLS coefficients"? It would of great help. Indeed, some referees  
did not like my overlapping regressions because of the bias cused by  
the MA errors in the point estimates. (My regressions were of the  
type: xtreg, fe cluster) Therefore, if I can justify it would be just  
perfect.

Any decent econometrics textbook discusses the consequences of  
violating the IID error assumption (usually when discussing  
generalized least squares, or robust standard errors, etc.) Generally  
speaking we know that AR(1) errors do not cause bias in point  
estimates. Nor do AR(2) errors, or AR(3) errors, etc. Now a finite MA  
process, if invertible, can always be expressed as an infinite-order  
AR process, so what you have is a OLS model with dummy variables with  
errors orthogonal to the regressors (by assumption of exogeneity). The  
fact that they can be expressed as a finite-order MA or an infinite- 
order AR should not matter. See Hansen and Hodrick's article on why  
overlapping data induce MA(j) where j is one less than the degree of  
overlap, and the solution being to use Newey-West with j lags. I don't  
have the H-H cite handy but have mentioned it not too long ago on this  
list.
I don't think -xtgls- will help, as I believe it only allows for AR(1)  
errors.
Kit
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------------------------------

Date: Mon, 1 Mar 2010 17:16:43 -0000
From: "Nick Cox" <n.j.cox@durham.ac.uk>
Subject: st: FAQ reminders

As long-time members will aver, the list works well almost all of the
time, especially if the criterion is getting help that is free, fast and
good. But all of us some of the time, and some of us all the time, might
helpfully pay a little more attention to well-meant advice in the FAQ,
intended in the best interests of all. (The URL for the FAQ appears at
the bottom of every Statalist posting.) 

Below my signature please find various extracts from the FAQ signalling
some of the most common lapses. And -- if you've never read it -- please
do look through the complete FAQ before making your first posting! 

Nick 
n.j.cox@durham.ac.uk 

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Clear questions
===============

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===============================================

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=======================

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------------------------------

Date: Mon, 1 Mar 2010 17:35:27 +0000
From: "Burak Darbaz" <infinisafricae@hotmail.com>
Subject: st: Panel LM Unit Root Test with Heterogenous Structural Breaks

Hello,

Does anybody have a code for Im, Lee & Tieslau (2005) panel LM unit root
test with het. structural breaks? I need it for testing unemployment
hysteresis as a part of my empirical project. I was able to find Gauss and
RATS codes but no chance for STATA. Otherwise, is there any alternatives
(besides clemao_io and zandrews)?

Thanks a lot,

Regards

Burak Darbaz

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------------------------------

Date: Mon, 1 Mar 2010 18:23:44 +0100
From: Carolina Lennon <carolina.lennon@gmail.com>
Subject: Re: st: re: Solving the moving average in the error structure in a

- --000e0ce0d6e8e496e60480c08255
Content-Type: text/plain; charset=ISO-8859-1

Great Kit, I found the reference.

Hansen, L.P., Hodrick, R.J.. "Forward Exchange-Rates As Optimal Predictors
of Future Spot Rates - An Econometric-Analysis." Journal of Political
Economy 88: 829-853, 1980.

Many thanks
Carol

2010/3/1 Christopher F Baum <baum@bc.edu>

> <>
> Carolina said
>
>
> I know that the following question is a little out of scope (since it does
> not relate to the stata commands), but just in case it is easy for you to
> reply...Do you know where I can find a reference justifying "that there is
> no reason for a MA error structure to induce bias in the OLS coefficients"?
> It would of great help. Indeed, some referees did not like my overlapping
> regressions because of the bias cused by the MA errors in the point
> estimates. (My regressions were of the type: xtreg, fe cluster) Therefore,
> if I can justify it would be just perfect.
>
> Any decent econometrics textbook discusses the consequences of violating
> the IID error assumption (usually when discussing generalized least squares,
> or robust standard errors, etc.) Generally speaking we know that AR(1)
> errors do not cause bias in point estimates. Nor do AR(2) errors, or AR(3)
> errors, etc. Now a finite MA process, if invertible, can always be expressed
> as an infinite-order AR process, so what you have is a OLS model with dummy
> variables with errors orthogonal to the regressors (by assumption of
> exogeneity). The fact that they can be expressed as a finite-order MA or an
> infinite-order AR should not matter. See Hansen and Hodrick's article on why
> overlapping data induce MA(j) where j is one less than the degree of
> overlap, and the solution being to use Newey-West with j lags. I don't have
> the H-H cite handy but have mentioned it not too long ago on this list.
> I don't think -xtgls- will help, as I believe it only allows for AR(1)
> errors.
> Kit
>
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>



- -- 
Carolina Lennon

Mobile in Austria:  (43) 06 76 59 24 553
Office at Wiiw in Vienna:  (43) 01 533 66 10 86
Institute website: http://www.wiiw.ac.at
Personal website: http://carolina.lennon.research.googlepages.com/
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- --000e0ce0d6e8e496e60480c08255--

------------------------------

Date: Mon, 1 Mar 2010 11:41:11 -0600
From: Dana Chandler <dchandler@gmail.com>
Subject: st: Text editor that has automatic table of contents?

Hello fellow statalisters -

I just recently started using Notepad++ and am very happy with the
editor (especially after figuring out how to run do-lines from within
the program http://s281191135.onlinehome.us/2008/20080427-stata.html).

However, one thing that would be really great to have from a text
editor is an automatically generated Table of Contents. For example, I
frequently write my do-files in indented sections (e.g., prepare data,
clean data, analysis 1, etc.). Some LaTeX editors make use of the
section/subsection declarations to create a Table of Contents that you
can see and point-click to while editting.

Are there any text editors that utilize indentation to show the first
level or two of heirarchy so that I could have a sense of the whole
do-file? Also - even if you don't know of any text editors, are there
any tips that people who write their do-files in sections have to
offer for keeping track of the structure of very lengthy do-files?

Thanks in advance,
Dana
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------------------------------

Date: Mon, 1 Mar 2010 17:37:02 +0000
From: =?ISO-8859-1?Q?Maximiliano_M=E9ndez_Parra?= <mm273@sussex.ac.uk>
Subject: st: Fwd: Saving results in program/loop

- --0016367b689e6ef5f00480c0b28a
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable

Dear all,

I am trying to do a Monte Carlo experiment. Inside the program there is a
loop that performs a given regression 100 times with different
specifications for each of the simulations (5000). At the end, the program
pick up the minimum t statistic from each of the 100 set of simulations to
form a distribution . The problem I have is that I want to know from which
of those 100 regressions the minimum t stat come from. Therefore, I need to
save the intermediate results. I've tried with postfile, however, it only
saves the last set of 100 regressions and I want to have all of them. I've
tried putting the commands inside and outside the loop but I failed. Or at
least, if it is not possible to save the intermediate results, I would like
to know if there is some way of associating those minimum t stats with a
give iteration inside the loop.

Can you help me?

My program looks like this

program seascrit1, rclass

version 10.0

drop _all

set obs 300

*More commands...*

forvalues i=3D1/100{

*More commands...*

reg XXX YYY ZZZ SSS....

test l.z3t l.z4t

scalar Fa`i'=3Dr(F)

test l.z5t l.z6t

scalar Fb`i'=3Dr(F)

test l.z7t l.z8t

scalar Fc`i'=3Dr(F)

test l.z9t l.z10t

scalar Fd`i'=3Dr(F)

test l.z11t l.z12t

scalar Fe`i'=3Dr(F)

scalar ba`i' =3D (_coef[l.z1t])/_se[l.z1t]

scalar bb`i' =3D (_coef[l.z2t])/_se[l.z2t]

}

*end of loop

return scalar b1...

return scalar b2...

....

scalar drop _all

end

simulate tbr=3Dr(tbr) b1=3Dr(b1) b2=3Dr(b2) b3=3Dr(b3) b4=3Dr(b4) b5=3Dr(b5=
) b6=3Dr(b6)
b7=3Dr(b7), reps(5000) : seascrit1


- --=20
Maximiliano M=E9ndez Parra
mm273@sussex.ac.uk




- --=20
Maximiliano M=E9ndez Parra
maximilianomp@gmail.com

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- --0016367b689e6ef5f00480c0b28a--

------------------------------

Date: Mon, 1 Mar 2010 17:57:44 -0000
From: "Nick Cox" <n.j.cox@durham.ac.uk>
Subject: st: RE: Text editor that has automatic table of contents?

This may seem too obvious, but I don't think you need any _special_
features for this (although no disrespect to any editor that does offer
this support). 

1. Use comments and/or blank lines to flag subdivisions. 

2. Invent your own conventions for section headings. 

3. If you use 1 or 2, then any decent editor will let you see only lines
of a certain form temporarily or let you jump between elements of a
certain form using some regular expression or other feature. 

In preparing a paper, I use !!! as a searchable flag for stuff that I
know needs to be filled in later. The trick clearly is to use something
that doesn't have a meaning otherwise. !! wouldn't qualify! ### or @@@
are other simple examples (for me). 

4. Subdivide the do file so that the details are in separate files with
informative names. Then use the master/mistress do file as a guide to
structure. 

5. Too many levels of nesting are as likely to hinder understanding as
help it. 

6. Never devise a scheme too complicated to explain to anyone else in a
minute. 

Nick 
n.j.cox@durham.ac.uk 

Dana Chandler

I just recently started using Notepad++ and am very happy with the
editor (especially after figuring out how to run do-lines from within
the program http://s281191135.onlinehome.us/2008/20080427-stata.html).

However, one thing that would be really great to have from a text
editor is an automatically generated Table of Contents. For example, I
frequently write my do-files in indented sections (e.g., prepare data,
clean data, analysis 1, etc.). Some LaTeX editors make use of the
section/subsection declarations to create a Table of Contents that you
can see and point-click to while editting.

Are there any text editors that utilize indentation to show the first
level or two of heirarchy so that I could have a sense of the whole
do-file? Also - even if you don't know of any text editors, are there
any tips that people who write their do-files in sections have to
offer for keeping track of the structure of very lengthy do-files?

Thanks in advance,
Dana
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------------------------------

Date: Mon, 1 Mar 2010 12:59:54 -0500
From: Christopher Baum <baum@bc.edu>
Subject: re: st: Fwd: Saving results in program/loop

I am trying to do a Monte Carlo experiment. Inside the program there is a
loop that performs a given regression 100 times with different
specifications for each of the simulations (5000). At the end, the program
pick up the minimum t statistic from each of the 100 set of simulations to
form a distribution . The problem I have is that I want to know from which
of those 100 regressions the minimum t stat come from. Therefore, I need to
save the intermediate results. I've tried with postfile, however, it only
saves the last set of 100 regressions and I want to have all of them. I've
tried putting the commands inside and outside the loop but I failed. Or at
least, if it is not possible to save the intermediate results, I would like
to know if there is some way of associating those minimum t stats with a
give iteration inside the loop.

ssc type zandrews.ado

for an example of how to do this.

Kit Baum   |   Boston College Economics and DIW Berlin   |   http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming   |   http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata   |   http://www.stata-press.com/books/imeus.html


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------------------------------

Date: Mon, 1 Mar 2010 19:04:15 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: RE: Text editor that has automatic table of contents?

<>

" However, one thing that would be really great to have from a text
editor is an automatically generated Table of Contents."


In UltraEdit, you can assign bookmarks and give them names. Below the text,
you can open a small window "bookmark viewer" where you see the names and
can jump to them by double-clicking. Very neat! Those bookmarks persist,
even after the text file has been closed, btw.



HTH
Martin

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Dana Chandler
Sent: Montag, 1. M�rz 2010 18:41
To: statalist@hsphsun2.harvard.edu
Subject: st: Text editor that has automatic table of contents?

Hello fellow statalisters -

I just recently started using Notepad++ and am very happy with the
editor (especially after figuring out how to run do-lines from within
the program http://s281191135.onlinehome.us/2008/20080427-stata.html).

However, one thing that would be really great to have from a text
editor is an automatically generated Table of Contents. For example, I
frequently write my do-files in indented sections (e.g., prepare data,
clean data, analysis 1, etc.). Some LaTeX editors make use of the
section/subsection declarations to create a Table of Contents that you
can see and point-click to while editting.

Are there any text editors that utilize indentation to show the first
level or two of heirarchy so that I could have a sense of the whole
do-file? Also - even if you don't know of any text editors, are there
any tips that people who write their do-files in sections have to
offer for keeping track of the structure of very lengthy do-files?

Thanks in advance,
Dana
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------------------------------

Date: Mon, 1 Mar 2010 13:11:09 -0500
From: Austin Nichols <austinnichols@gmail.com>
Subject: Re: st: Endogenous Regressors Predicted by the Same IV

Lloyd Dumont <lloyddumont@yahoo.com> :
Kit points out that your equation is underidentified, but if you are
willing to assume that the products of Z_1 with X_4,.. X_10 are
uncorrelated with the error, you have 7 additional excluded
instruments to use.  Run IV first using e.g. -ivreg2- (on SSC)
ignoring the binary outcome, as the diagnostics for linear IV are
better developed and will give you a sense of dp/dX in any case. The
key diagnostics here are weak IV stats and the overid test, since you
have a pretty weak argument for your exclusion restrictions and no
guarantee of strong correlations. Then you can go to -ivprobit- or
- -cmp- (SSC) or the like, if linear IV looks good.

On Mon, Mar 1, 2010 at 11:01 AM, Kit Baum <baum@bc.edu> wrote:
> No can do. This is a textbook case of under(un)identification. You need at least three Z variables to identify the equation, whether or not the estimation technique is OLS, probit, etc.

On Mon, Mar 1, 2010 at 10:48 AM, Lloyd Dumont <lloyddumont@yahoo.com> wrote:
> I�m pretty sure that what we�re trying to do is mathematically estimable under certain assumptions.  So, we are trying to figure out the syntax for the estimating procedure.  And, then we�d like to clarify the assumptions that have to hold for us to accept the estimates.
>
> We are ultimately trying to estimate a dep var we will call Y_dep.  Y_dep is being predicted by X_1, X_2, �X_10.  But, X_1, X_2, and X_3 are all endogenous.  We believe they can all be predicted by the same instrumental variable, Z_1.  And, furthermore, we are willing to accept that Z_1 has no direct effect on Y_dep beyond its effects through X_1, X_2, and X_3.

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------------------------------

Date: Mon, 01 Mar 2010 11:22:04 -0700
From: "Luciana Zilberman" <lzilberman@salud.unm.edu>
Subject: st: vector with weighted observations question

This is a MIME message. If you are reading this text, you may want to 
consider changing to a mail reader or gateway that understands how to 
properly handle MIME multipart messages.

- --=__Part765CBCDC.0__=
Content-Type: text/plain; charset=US-ASCII
Content-Transfer-Encoding: quoted-printable

I have the following question: I have a dataset I am weighting using the  =
[aw=3Dweight] command and I was wondering if there is a way to see each =
weighted observation for a given variable in Stata (e.g., a vector of =
weighted observations). The "sum variable1 [aw=3Dweight] " gives me the =
weighted mean for variable1 but I am also interested in getting a vector =
that shows the weighted observations. I would really appreciate any help.
=20
Thank you.
Luciana

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------------------------------

Date: Mon,  1 Mar 2010 14:33:48 -0500
From: Ashlie Delshad <abelmore@purdue.edu>
Subject: st: expected values after xtpcse

Hello,

I would like to generate specific expected values for my DV given key variables 
on one of my IVs - holding all other IVs constant.  I have done this before in 
STATA, but I'm having difficulty remembering which commands I need to use.  I 
am running a panel corrected Prais-Winsten model(xtpcse). Any help would be 
much appreciated.

Ashlie Delshad, Ph.D. Student
Purdue University 
Department of Political Science
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------------------------------

Date: Mon, 1 Mar 2010 19:34:28 +0000
From: "Burak Darbaz" <infinisafricae@hotmail.com>
Subject: st: RE: I need help with Extreme Bound Analysis

Here's an easy command for Leamer's Extreme Bound Analysis by Gregorio
Impavido.

http://ideas.repec.org/c/boc/bocode/s347401.html

Burak Darbaz

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Kwame
Sent: 01 March 2010 03:41
To: statalist@hsphsun2.harvard.edu
Subject: st: I need help with Extreme Bound Analysis






Dear Statalist Veterans:


I
am new to Stata but have a project requiring eba (Extreme Bound
Analysis). The equation I am estimating is in the form:


Y = a +BiI+BmM+BzZ+u

 

Y is the dependent variable 

I is the vector of free variables (one variable in the present)

M is a vector of four variables of interest

Z is a vector of control variables
(ten in this case)


I want Stata to
take tow Z variables in each combination (with the I variable and one M
variable) but have been getting syntax
errors as I try. Below are two questions I'd like you to help me with based
upon what
I've explained above: 



What is the correct command to run the
     model for each of the variables(M)of interest?Is it possible to run eba
for all the
     four variables of interest with a single command and if so what will it
be?
I appreciate any help you can offer me with this.


Kwame
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------------------------------

Date: Mon, 1 Mar 2010 20:16:13 +0000
From: Neil Shephard <nshephard@gmail.com>
Subject: Re: st: Text editor that has automatic table of contents?

On Mon, Mar 1, 2010 at 5:41 PM, Dana Chandler <dchandler@gmail.com> wrote:
> Hello fellow statalisters -
>
> I just recently started using Notepad++ and am very happy with the
> editor (especially after figuring out how to run do-lines from within
> the program http://s281191135.onlinehome.us/2008/20080427-stata.html).
>
> However, one thing that would be really great to have from a text
> editor is an automatically generated Table of Contents. For example, I
> frequently write my do-files in indented sections (e.g., prepare data,
> clean data, analysis 1, etc.). Some LaTeX editors make use of the
> section/subsection declarations to create a Table of Contents that you
> can see and point-click to while editting.
>
> Are there any text editors that utilize indentation to show the first
> level or two of heirarchy so that I could have a sense of the whole
> do-file?

I'm not aware of anything that does this, and to be honest I suspect
it may well be unique to LaTeX anyway.  Editors that show the
formatted output of LaTeX are in essence compiling it on the fly to
display it (the only one I have experience of is Gummi for Linux, see
http://gummi.midnightcoding.org/).  Often you have to compile LaTeX
source a couple of times to get all the referencing correct too.
Do-files are never compiled in this way, they're simply read
line-by-line by Stata.


>  Also - even if you don't know of any text editors, are there
> any tips that people who write their do-files in sections have to
> offer for keeping track of the structure of very lengthy do-files?

Stata NetCourse 101 and the subsequent 151 are good courses and
provide good advice on organising you work-flow with Stata.

The basic approach though is to avoid writing really long do-files.
Simply write a small do-file for each specific task and have a
"master" do-file that calls each in turn.

You might also find some of the advice in
http://www.stata-press.com/books/wdaus.html on managing/organising
do-files useful too.

Neil

- -- 
"... no scientific worker has a fixed level of significance at which
from year to year, and in all circumstances, he rejects hypotheses; he
rather gives his mind to each particular case in the light of his
evidence and his ideas." - Sir Ronald A. Fisher (1956)

Email - nshephard@gmail.com
Website - http://slack.ser.man.ac.uk/
Photos - http://www.flickr.com/photos/slackline/
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------------------------------

Date: Mon, 1 Mar 2010 14:39:38 -0600
From: "Qian, Yiming" <yiming-qian@uiowa.edu>
Subject: st: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering

Dear Statalist,

I use "estimates store + suest + test" to compare regression coefficients between two samples.� It works fine until I tried to adjust clustering in the regressions. Below are detailed description of the problem. Is there a way to can get around this problem using "suest" or some alternative commands?

I ran the same regression for two groups (male vs. female):
Y = a1*x1 + a2*x2 + a3*x3 + ....
I want to test:
1.����� The joint hypothesis that a1 and a2 are the same b/w the two groups.
2.����� The hypothesis that a1/a2 is the same b/w the two groups.


The following stata codes work fine:� 
reg y x1 x2 x3 x4 if female==0
estimates store male
reg y x1 x2 x3 x4 if female==1
estimates store male
suest male female
test ([male_mean]_b[x1] = [female_mean]_b[x1]) ([male_mean]_b[x2] = [female_mean]_b[x2])
testnl [male_mean]_b[x1]/[male_mean]_b[x2] = [female_mean]_b[x1]/[female_mean]_b[x2])

However, if I add cluster() to the two regressions, I got error messages.� 
reg y x1 x2 x3 x4 if female==0, cluster(family)
estimates store male
reg y x1 x2 x3 x4 if female==1, cluster(family)
estimates store male
suest male female

The error message is:
"male was estimated with cluster(family). 
re-estimate without the cluster() option, and 
specify the cluster() option with suest.
r(322);"


Thank you very much!
Yiming Qian






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------------------------------

Date: Mon, 1 Mar 2010 21:51:17 +0100
From: "Martin Weiss" <martin.weiss1@gmx.de>
Subject: st: RE: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering

<>


"The error message is:
"male was estimated with cluster(family). 
re-estimate without the cluster() option, and 
specify the cluster() option with suest.
r(322);""



Just follow Stata`s advice, I would say:

*******
sysuse auto, clear
reg price weight length if foreign
est store for
reg price weight length if !foreign
est store dom
suest for dom, cluster(rep)
test ([for_mean]_b[weight ] = [dom_mean]_b[weight ]) ([for_mean]_b[length ]
= [dom_mean]_b[length ])
testnl ([for_mean]_b[weight ] / [dom_mean]_b[weight ]) =
([for_mean]_b[length ] /[dom_mean]_b[length ])
*******


HTH
Martin

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Qian, Yiming
Sent: Montag, 1. M�rz 2010 21:40
To: statalist@hsphsun2.harvard.edu
Subject: st: using estimate store + suest+test to compare regression
coefficients between two samples, how to adjust for clustering

Dear Statalist,

I use "estimates store + suest + test" to compare regression coefficients
between two samples.� It works fine until I tried to adjust clustering in
the regressions. Below are detailed description of the problem. Is there a
way to can get around this problem using "suest" or some alternative
commands?

I ran the same regression for two groups (male vs. female):
Y = a1*x1 + a2*x2 + a3*x3 + ....
I want to test:
1.����� The joint hypothesis that a1 and a2 are the same b/w the two groups.
2.����� The hypothesis that a1/a2 is the same b/w the two groups.


The following stata codes work fine:� 
reg y x1 x2 x3 x4 if female==0
estimates store male
reg y x1 x2 x3 x4 if female==1
estimates store male
suest male female
test ([male_mean]_b[x1] = [female_mean]_b[x1]) ([male_mean]_b[x2] =
[female_mean]_b[x2])
testnl [male_mean]_b[x1]/[male_mean]_b[x2] =
[female_mean]_b[x1]/[female_mean]_b[x2])

However, if I add cluster() to the two regressions, I got error messages.� 
reg y x1 x2 x3 x4 if female==0, cluster(family)
estimates store male
reg y x1 x2 x3 x4 if female==1, cluster(family)
estimates store male
suest male female

The error message is:
"male was estimated with cluster(family). 
re-estimate without the cluster() option, and 
specify the cluster() option with suest.
r(322);"


Thank you very much!
Yiming Qian






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------------------------------

Date: Mon, 1 Mar 2010 20:53:30 +0000
From: Clive Nicholas <clivelists@googlemail.com>
Subject: Re: st: expected values after xtpcse

Ashlie Delshad wrote:

> I would like to generate specific expected values for my DV given key variables
> on one of my IVs - holding all other IVs constant. �I have done this before in
> STATA, but I'm having difficulty remembering which commands I need to use. �I
> am running a panel corrected Prais-Winsten model(xtpcse). Any help would be
> much appreciated.

- -help adjust-?

- -- 
Clive Nicholas

[Please DO NOT mail me personally here, but at
<clivenicholas@hotmail.com>. Please respond to contributions I make in
a list thread here. Thanks!]

"My colleagues in the social sciences talk a great deal about
methodology. I prefer to call it style." -- Freeman J. Dyson.

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------------------------------

Date: Mon, 1 Mar 2010 15:57:08 -0500
From: Daniel Miller <danielpmiller@gmail.com>
Subject: Re: st: lags with multiply imputed panel data

- --00504502cc540586840480c37e58
Content-Type: text/plain; charset=ISO-8859-1

Hi Johan --- thank you for your response. I had set something similar up to
get around the problem before --- but was curious if there was a way to sort
the data properly.
In any case, thank you for the information.

Dan

On Mon, Mar 1, 2010 at 9:50 AM, Johan Hellstrom
<johan.hellstrom@pol.umu.se>wrote:

> If the L. prefix does not work, you can see if creating your lagged
> treatment variable manually will help:
>
> bysort idnum (wave): gen lag_ratecata1=ratecata1[_n-1]
>
> Best,
> Johan
>
>
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- --00504502cc540586840480c37e58--

------------------------------

Date: Mon, 1 Mar 2010 16:00:37 -0500
From: Daniel Miller <danielpmiller@gmail.com>
Subject: Re: st: lags with multiply imputed panel data

- --000e0cd2e1a87d20850480c38a2b
Content-Type: text/plain; charset=ISO-8859-1

Hi Nick, thank you for replying.

As I noted in the original email, I am not sure the issue is that the time
variable is not appropriately set, but rather that the data are not sorted
properly.
I am able to set lags using L. or L2. just fine in any of the individual
imputed datasets. It is only when I try a combining algorithm using
micombine or mim:
that I get an error message like:

e.g.
mim: xtreg fwork l.ratecata1, fe
- -> _mj==1
- -> xtreg fwork l.ratecata1, fe
not sorted
r(5);

Thanks,
Dan


On Mon, Mar 1, 2010 at 9:57 AM, Nick Cox <n.j.cox@durham.ac.uk> wrote:

> If L. "does not work", whatever that means precisely, then what this
> yields is a beast of unpredictable shape.
>
> Better to set the time variable to something appropriate, and let any
> missings in those terms be explicit.
>
> Nick
> n.j.cox@durham.ac.uk
>
> Johan Hellstrom
>
> If the L. prefix does not work, you can see if creating your lagged
> treatment variable manually will help:
>
> bysort idnum (wave): gen lag_ratecata1=ratecata1[_n-1]
>
>
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- --000e0cd2e1a87d20850480c38a2b--

------------------------------

Date: Tue, 2 Mar 2010 11:33:04 +1300
From: Thu Phuong Truong <Phuong.Truong@vuw.ac.nz>
Subject: st: RE: AW: bootstrap in factor analysis

Dear Martin,

Thank so much for your kind help.

Yours sincerely,

Phuong

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
Sent: Tuesday, 2 March 2010 2:08 a.m.
To: statalist@hsphsun2.harvard.edu
Subject: st: AW: bootstrap in factor analysis


<> 

Type -ereturn list- after the factor command to see the available returned
results:


*************
webuse bg2, clear
factor bg2cost1-bg2cost6, factors(2) pcf
eret li
*************



HTH
Martin

- -----Urspr�ngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Thu Phuong
Truong
Gesendet: Sonntag, 28. Februar 2010 23:21
An: statalist@hsphsun2.harvard.edu
Betreff: st: bootstrap in factor analysis

Dear Martin and statalister,

Thank so much for getting back to me. I am sorry that I did not make it
clear in my previous email. I could do bootstrap for regression. However, I
have trouble with factor analysis as I do not know what I should include in
the exp_list.

For example
bootstrap exp_list, reps(1000): factor reform_index analyst_index
herfindahl5_index ceochair_index brdsize_index brdindp1a ac_index if
firmyeartestqualified==1, pcf

What should I include as exp_list in order to test whether the factor
loadings are significantly from zero?

Thank so much for your help.

Yours sincerely,

Phuong

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------------------------------

Date: Mon, 1 Mar 2010 15:51:11 -0700
From: "Buzz Burhans" <buzzb3@earthlink.net>
Subject: st: RE: Text editor that has automatic table of contents?

Dana,

A test editor called EmEditor has a plug in that automates outlining.
EmEditor is one of two text editors I have used and liked, it is Windows
based, though I run XP Professional, don't know how well it works with Vista
or W-7

http://www.emeditor.com/

You've had a couple of suggestions to use a Master -do- file that calls
subordinate -do- files - that is excellent advice that I think I picked up
on when I took the Net Course 101 or 151 about 10 or more years ago. The Net
courses are great!!

Related to using Master files, I have also used a text editor called Crimson
Editor that allows you to have a "project" pane open on the side, where I
keep a sort of outline of the Master file and the subordinate -do- files it
calls.  It works similarly to having an editor, but allows the files to be
separate rather than sections of a single outlined file.

http://www.crimsoneditor.com/

Buzz





Buzz Burhans, Ph.D. 

Dairy-Tech Group
So. Albany, VT / Twin Falls ID

Phone: 802-755-6842
Cell: 208-320-0829
Fax VT: 802-755-6842
Fax ID: 208-735-1289

Email: buzzb3@earthlink.net

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Dana Chandler
Sent: Monday, March 01, 2010 10:41 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: Text editor that has automatic table of contents?



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------------------------------

Date: Mon, 1 Mar 2010 23:10:54 -0000
From: Z.Ou@warwick.ac.uk
Subject: st: Question on survey data analysis

Dear Statalists, I am new to stata so please, please forgive me if my
question seems too easy for you��I designed a survey about loyalty schemes
(e.g. tesco clubcard that sort of programmes) for my economics research
project, but not sure how to compute multiple choice questions in the
questionnaire.

One of my questions was: ��Why don��t you join any loyalty schemes?�� and
my list of answers include: a) poor customer service, b) unachievable
rewards, c) unrealistic points, d) too much marketing communications, e)
redeeming schemes too complicated, f) choice of rewards available and g)
others, i.e. 7 options in total.

Respondents were asked to tick all that apply. I want to see which are the
most deterring factors of the list that make these students not want to
join loyalty schemes. Could someone give me any hints? Do I have to create
a new dummy variable for each of the seven alternatives?

A similar question asked which, if any, respondents are aware of out of a
list of ten different stores/retailers who have loyalty schemes. Again, do
I have to treat each option as a independent dummy?

Also do I have to declare data type as survey data to carry out any
further analysis? Or is it alright for me to do simple regression analysis
without letting stata know it's survey data I'm working with? Does it
affect my results?

Thanks very much for your time!!!
Michelle

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------------------------------

Date: Mon, 1 Mar 2010 22:20:52 -0600
From: "Qian, Yiming" <yiming-qian@uiowa.edu>
Subject: st: RE: RE: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering

Martin,

Thank you very much for your kind help!  It answers my question perfectly!

I have a follow-up question: can I use similar tests for median regressions (qreg)?  If not suest+test, how to compare coefficients across models for median regressions?

I tried the following codes:
qreg y x1 x2 x3 x4 if female==0
estimates store male
qreg y x1 x2 x3 x4 if female==1
estimates store male
suest male female

I got the following error message:

"unable to generate scores for model male
suest requires that predict allow the score option
r(322);"

Thanks a lot!
Yiming 


- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
Sent: Monday, March 01, 2010 2:51 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: using estimate store + suest+test to compare regression coefficients between two samples, how to adjust for clustering


<>


"The error message is:
"male was estimated with cluster(family). 
re-estimate without the cluster() option, and 
specify the cluster() option with suest.
r(322);""



Just follow Stata`s advice, I would say:

*******
sysuse auto, clear
reg price weight length if foreign
est store for
reg price weight length if !foreign
est store dom
suest for dom, cluster(rep)
test ([for_mean]_b[weight ] = [dom_mean]_b[weight ]) ([for_mean]_b[length ]
= [dom_mean]_b[length ])
testnl ([for_mean]_b[weight ] / [dom_mean]_b[weight ]) =
([for_mean]_b[length ] /[dom_mean]_b[length ])
*******


HTH
Martin

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Qian, Yiming
Sent: Montag, 1. M�rz 2010 21:40
To: statalist@hsphsun2.harvard.edu
Subject: st: using estimate store + suest+test to compare regression
coefficients between two samples, how to adjust for clustering

Dear Statalist,

I use "estimates store + suest + test" to compare regression coefficients
between two samples.� It works fine until I tried to adjust clustering in
the regressions. Below are detailed description of the problem. Is there a
way to can get around this problem using "suest" or some alternative
commands?

I ran the same regression for two groups (male vs. female):
Y = a1*x1 + a2*x2 + a3*x3 + ....
I want to test:
1.����� The joint hypothesis that a1 and a2 are the same b/w the two groups.
2.����� The hypothesis that a1/a2 is the same b/w the two groups.


The following stata codes work fine:� 
reg y x1 x2 x3 x4 if female==0
estimates store male
reg y x1 x2 x3 x4 if female==1
estimates store male
suest male female
test ([male_mean]_b[x1] = [female_mean]_b[x1]) ([male_mean]_b[x2] =
[female_mean]_b[x2])
testnl [male_mean]_b[x1]/[male_mean]_b[x2] =
[female_mean]_b[x1]/[female_mean]_b[x2])

However, if I add cluster() to the two regressions, I got error messages.� 
reg y x1 x2 x3 x4 if female==0, cluster(family)
estimates store male
reg y x1 x2 x3 x4 if female==1, cluster(family)
estimates store male
suest male female

The error message is:
"male was estimated with cluster(family). 
re-estimate without the cluster() option, and 
specify the cluster() option with suest.
r(322);"


Thank you very much!
Yiming Qian






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------------------------------

Date: Tue, 02 Mar 2010 08:11:15 +0100
From: Maurizio Pisati <maurizio.pisati@unimib.it>
Subject: Re: st: using spmap and option "point"

Dear Ana,
your only chance is to add a variable that identifies regions to 
"file2.dta", and then use it in suboption -point()- to select only the 
stores located in regions B or C. To generate such variable, you might 
want to use a point-in-polygon algorithm -- an example of which, coded 
in Mata as function -sp_pips-, can be found in the -spgrid- Stata 
program (ssc install spgrid).
Best wishes,
Maurizio




Il 01/03/10 09.35, Vitorino, Maria Ana ha scritto:
> Dear statalist users,
>
> Is the following possible?
>
> I have 2 files:
>
> *file1 is something like:
>
> region populationsize  id
> A            ...                	  1
> B            ...              		  2
> C           ...               	  3
>
> (I also have a file with the region coordinates so that I can use spmap)
>
> *file 2 is something like:
>
> store_id  xcoord  ycoord
> 100          ...			...
> 201           ...		...
> 345          ...			...
> 411           ...		...
> 544          ...			...
>
>
>
> I would like to do a map with the stores superimposed on the map but only for the stores that are located in region B or C (note that I don't have that information on file2, otherwise it would be easy to do), excluding store 345 (irrespective of where it is located).
>
> If I do something like the following, the problem is that all the stores (even the ones that are not located in regions B or C) show up...and I only want the ones located in regions B or C.
>
> spmap populationsize if region=="B" | region=="C" using file1coord, id(id) point(data("file2.dta") xcoord(xcoord) ycoord(ycoord) fcolor(emerald) select(drop if store_id==345))
>
> How can I modify this command line to achieve what I'm looking for?
>
> Any help is appreciated.
> Thanks!
>
> Ana
>
>
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------------------------------

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