st: Kaplan Meier graph
Hi, Patricia,
you can just add commands which define the
linestyle, linecolor, etc. to overwrite the default options.
sts graph, by (sex) lcolor(black red)
lpattern(dash dash) lwidth(medium thin) connect(stairstep direct)
cheers,
Zhiqiang
Date: Fri, 9 Dec 2005 02:22:26 +0100 (CET)
From: Patricia Vera Rojas <[email protected]>
Subject: st: Kaplan Meier graph
Hi all,
I want to graph survivor function and hazard rates by
different groups. For instance:
sts graph, by(sexo)
but I need the lines of sexo=0 and sexo=1 be differentiated
not by colour but for different types of lines, like
continuous or spacing lines or another types that allow me
to understand the differences between both groups in a
white-black printing.
How can I do it?
Thnaks a lot,
Patricia
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------------------------------
Date: Thu, 8 Dec 2005 17:54:42 -0800 (PST)
From: "Sunhwa Lee" <[email protected]>
Subject: Re: st: maximum likelihood procedures for oprobit
Thank you very much for your answer.
> First off, why do you want to write your own program when Stata
> already has one? Even if you get your program to work, Stata's will
> likely be quicker, more efficient and less likely to encounter problems.
I am working on a more structural model that restricts the way the
threshold/cutoff points are calculated. So, writing up a program which is
identical to oprobit, is just the first step to my work.
> Second, while you may have the formulas right, that doesn't mean your
> code is the same as oprobit's. The programs go through an iterative
> procedure, and some procedures will work better than others.
In fact, I am really concerned about this iteration procedures, as the
estimates on some of my dummy variables are a lot different depending on
the tolerance levels.
> Try adding the difficult option to your ml maximize commands, e.g.
> ml maximize, difficult
> According to the help, "difficult specifies that a different stepping
> algorithm be used in nonconcave regions. There is no
> guarantee that difficult will work better than the default; sometimes
> it is better, and sometimes it is worse. You should use the
> difficult option only when the default stepper declares convergence
> and the last iteration is "not concave", or when the default
> stepper is repeatedly issuing "not concave" messages and
> only producing tiny improvements in the log likelihood."
>
> You could also try playing around with the technique option. Type
> -help maximize- for more details.
I tried "difficult" as well and from "maximize" help, the only two that
are clearly stated are tolerance and Itorelance levels, which I already
played around with.
I found "oprobit.ado" file from stata now and am gonna try to depuzzle
it. Thank you very much again...
Sunhwa
**************************************
Lee, Sunhwa
PhD Candidate
Department of Economics
University of California at Davis
Davis, CA, 95616
(Office) 109 SSH
(Phone) (530)752-2845
**************************************
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------------------------------
Date: Thu, 8 Dec 2005 21:15:19 -0500
From: "David Roodman \([email protected]\)" <[email protected]>
Subject: RE: st: maximum likelihood procedures for oprobit
Torgne Middendorf wrote:
I know this question has been adressed before but no one really answered how
to use dummy variables with the xtabond2 command the right way. In xtabond,
there was an option called "diffvars" to prevent Stata from differencing the
concerning variables. In xtabond2 there is a option called "passthru" but
this option only prevents Stata from differencing the instruments (whereas
another question arises, does "passthru" prevent Stata from differencing all
instruments listed after "iv or "gmm"?).
For an answer, see
http://www.stata.com/statalist/archive/2005-11/msg00275.html
- --David
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Sunhwa Lee
Sent: Thursday, December 08, 2005 8:55 PM
To: Richard Williams; [email protected]
Subject: Re: st: maximum likelihood procedures for oprobit
Thank you very much for your answer.
> First off, why do you want to write your own program when Stata
> already has one? Even if you get your program to work, Stata's will
> likely be quicker, more efficient and less likely to encounter problems.
I am working on a more structural model that restricts the way the
threshold/cutoff points are calculated. So, writing up a program which is
identical to oprobit, is just the first step to my work.
> Second, while you may have the formulas right, that doesn't mean your
> code is the same as oprobit's. The programs go through an iterative
> procedure, and some procedures will work better than others.
In fact, I am really concerned about this iteration procedures, as the
estimates on some of my dummy variables are a lot different depending on
the tolerance levels.
> Try adding the difficult option to your ml maximize commands, e.g.
> ml maximize, difficult
> According to the help, "difficult specifies that a different stepping
> algorithm be used in nonconcave regions. There is no
> guarantee that difficult will work better than the default; sometimes
> it is better, and sometimes it is worse. You should use the
> difficult option only when the default stepper declares convergence
> and the last iteration is "not concave", or when the default
> stepper is repeatedly issuing "not concave" messages and
> only producing tiny improvements in the log likelihood."
>
> You could also try playing around with the technique option. Type
> -help maximize- for more details.
I tried "difficult" as well and from "maximize" help, the only two that
are clearly stated are tolerance and Itorelance levels, which I already
played around with.
I found "oprobit.ado" file from stata now and am gonna try to depuzzle
it. Thank you very much again...
Sunhwa
**************************************
Lee, Sunhwa
PhD Candidate
Department of Economics
University of California at Davis
Davis, CA, 95616
(Office) 109 SSH
(Phone) (530)752-2845
**************************************
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------------------------------
End of statalist-digest V4 #2181
********************************
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Dr. Zhiqiang Feng
School of Geography and Geosciences
University of St Andrews
Irvine Building, North Street
St Andrews
Fife, Scotland
KY16 9AL
email: [email protected]
phone: 01334 463951
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