Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down at the end of May, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: Propensity Score Matching with Multiple Categorical Variables with Multiple Categories...Dummy Variables?


From   Marcello Pagano <pagano@hsph.harvard.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Propensity Score Matching with Multiple Categorical Variables with Multiple Categories...Dummy Variables?
Date   Sat, 14 Jul 2012 12:33:12 -0400

We can, Peter.  If the Listers want me to, I shall.

You can also vote with your feet; ignore the postings. Do not respond.

m.p.


On 7/14/2012 12:22 PM, Lachenbruch, Peter wrote:
I am also frustrated by anonymous posters.  Can we simple block such posts from appearing?  Marcello?

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steve Samuels [sjsamuels@gmail.com]
Sent: Saturday, July 14, 2012 6:28 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Propensity Score Matching with Multiple Categorical Variables with Multiple Categories...Dummy Variables?

Please take note of the FAQ section:

         • "It is long-standing practice on Statalist that most members, especially the most active members who supply a large fraction of the answers, post using their real names. This is one of the ways in which we show respect to others. So we discourage you from posting from behind fake names or identifiers. Such handles are particularly objectionable if they include the word “Stata” in some way.. "

I would add that "real name" means first and last name.

Steve
sjsamuels@gmail.com


On Jul 14, 2012, at 1:51 AM, TA Stat wrote:

Thanks everyone for advice.  I am figuring out how to collapse some
categories of each variable in a meaningful way for my research
question.  I will keep my eyes on additional advice from everyone.

Pete

On Fri, Jul 13, 2012 at 10:12 PM, Austin Nichols
<austinnichols@gmail.com> wrote:
Ariel and Pete--
Estimating a logit with dummies is one way to combine across distinct
combinations of the 15 observables to estimate a propensity score. A
fully nonparametric propensity score would include every possible
interaction as well, or simply compute the mean of treatment across
all cells (possibly millions of cells).  If any cells have pscore 0 or
1, and some are almost certain to be degenerate in that way, then you
must combine that cell with another; one way of doing that is using
the marginal across some subset of categories. The logit with no
interactions is one particular method of combining across cells.

sysuse auto
logit foreign i.rep78
predict p if e(sample)
egen m=mean(foreign), by(rep78)
su m p if p<.
* Note that if you do not restrict using if e(sample)
* the estimated p=.818 for rep78=1
* (taken from excl cat rep78=5) when it should be zero.
ta rep78, mi sum(foreign)
ta rep78, mi sum(m)
ta rep78, mi sum(p)

g fakecat=round(mpg,10)
logit foreign i.rep78##i.fakecat
predict p2 if e(sample)
egen m2=mean(foreign), by(rep78 fakecat)
su m2 p2 if p2<.


On Fri, Jul 13, 2012 at 10:19 AM, Ariel Linden, DrPH
<ariel.linden@gmail.com> wrote:
Hi Pete,

Since estimation of the propensity score is nothing more than a logistic (or
probit) regression model, you could leave the categorical variables as-is
and use the "i." prefix to denote that they are categorical, such as i.race.
The regression output will show you that the levels of the categorical
variable have been dealt with accordingly (including if any of the levels
are dropped from the model). See for example:

sysuse auto
logit foreign i.rep78

On the other hand, you could certainly create dummy variables for the
categorical variable. However, if you have a large number of covariates,
your dataset will start looking ugly in a hurry. In any case, your results
will be identical:

tab rep78, gen(rep78_)
logit foreign rep78_1- rep78_5

I hope this helps

Ariel

Date: Fri, 13 Jul 2012 10:06:14 +0700
From: TA Stat <tastat@gmail.com>
Subject: st: Propensity Score Matching with Multiple Categorical Variables
with Multiple Categories...Dummy Variables?

Dear All

In PS matching, I am wondering about how to handle multiple
categorical variables e.g. 15 variables.  Each variable has multiple
categories e.g. 3-5 categories.  Do I have to create dummy variables,
(n-1 for each variable), for all those categorical variables before
calculating propensity score?

Thanks
Pete
*
*   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/
*
*   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/


*
*   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/
*
*   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/


*
*   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/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index