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Re: st: RE: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: RE: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot
Date   Wed, 17 Apr 2013 20:22:47 +0100

Thanks for the details.

Your Stata is up-to-date.

Your -gllamm- is not up-to-date. See SSC for a version 10 years more
recent and install it using -ssc-.

. ssc type gllamm.ado
*! version 2.3.20 SRH 7 Sept 2011
program define gllamm, eclass

I can't say whether updating will fix your problem, but it will do no harm.

Nick
njcoxstata@gmail.com


On 17 April 2013 19:24, Sun, Wensheng <wsun@bcm.edu> wrote:
> Hi, please check the below regarding the gllamm I have installed. Thanks.
>
> . about
> Stata/IC 12.1 for Windows (64-bit x86-64)
> Revision 20 Mar 2013
> Copyright 1985-2011 StataCorp LP
> Total physical memory:     8344592 KB
> Available physical memory: 5329516 KB
> Single-user Stata perpetual license:
>        Serial number:  30120591501
>          Licensed to:  Wensheng Sun
>                        Baylor College of Medicine
> . which gllamm
> c:\ado\plus\g\gllamm.ado
> *! version 2.1.03 27oct2001   (TSJ-2: st0005)
>
>
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox [njcoxstata@gmail.com]
> Sent: Wednesday, April 17, 2013 12:22 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot
>
> It's -margins- that is complaining. That's part of official Stata. So, report
>
> . about
> . which gllamm
>
> to provide a fuller picture of what you have installed.
> Nick
> njcoxstata@gmail.com
>
>
> On 17 April 2013 17:40, Sun, Wensheng <wsun@bcm.edu> wrote:
>> Hi Joseph,
>>
>> Thank you very much for the code. However, it seems my gllamm is different from your. The following is the error message.
>>
>> . margins, at(_Igirl_1=(0 1) age=(0(0.5)2.5))
>> Warning: cannot perform check for estimable functions.
>> e(sample) does not identify the estimation sample
>> r(322);
>>
>> . margins , at(_Igirl_1 = (0 1) age = (0(0.5)2.5))
>> Warning: cannot perform check for estimable functions.
>> e(sample) does not identify the estimation sample
>> r(322);
>>
>> I thought I already download everything I can get from gllamm including gllapred, runmlwin, and many others. Please help.
>>
>> Thanks.
>>
>> Wensheng
>>
>> ________________________________________
>> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Joseph Coveney [stajc2@gmail.com]
>> Sent: Tuesday, April 16, 2013 9:06 PM
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: Re: xtmixed with log-transfered dependent variable: back to non-log on margins and marginsplot
>>
>> Wensheng Sun wrote:
>>
>> Hi, Please help. How to do post multilevel regression estimation after gllamm? I
>> tried "margins" command, it seems not work. Please fix it for me. Thanks.
>>
>> [snip]
>>
>> --------------------------------------------------------------------------------
>>
>> You could try something like that below.
>>
>> If a variable is not a factor variable (that is, if it is not included in the
>> model with the i.variable notation*), then it is considered by Stata to be a
>> continuous variable.  So, despite its being coded 0/1, _I_girl_1 is considered
>> by Stata to be a continuous variable.
>>
>> -margins- requires its first arguments to be factor variables--variables that
>> were in the model as i.variable.  Because _I_girl_1 is a continuous variable and
>> not a factor variable, you must treat it as a continuous variable when you refer
>> to it with -margins-.
>>
>> Joseph Coveney
>>
>> *-anova- and -manova- are notable exceptions.
>>
>>
>> [Model fitting omitted for brevity.  To see it, look at my most recent post in
>> this thread.]
>>
>> . margins , at(_Igirl_1 = (0 1) age = (0(0.5)2.5))
>> Warning: cannot perform check for estimable functions.
>>
>> Predictive margins                                Number of obs   =        198
>> Model VCE    : OIM
>>
>> Expression   : predict()
>>
>> 1._at        : age             =           0
>>                _Igirl_1        =           0
>>
>> 2._at        : age             =           0
>>                _Igirl_1        =           1
>>
>> 3._at        : age             =          .5
>>                _Igirl_1        =           0
>>
>> 4._at        : age             =          .5
>>                _Igirl_1        =           1
>>
>> 5._at        : age             =           1
>>                _Igirl_1        =           0
>>
>> 6._at        : age             =           1
>>                _Igirl_1        =           1
>>
>> 7._at        : age             =         1.5
>>                _Igirl_1        =           0
>>
>> 8._at        : age             =         1.5
>>                _Igirl_1        =           1
>>
>> 9._at        : age             =           2
>>                _Igirl_1        =           0
>>
>> 10._at       : age             =           2
>>                _Igirl_1        =           1
>>
>> 11._at       : age             =         2.5
>>                _Igirl_1        =           0
>>
>> 12._at       : age             =         2.5
>>                _Igirl_1        =           1
>>
>> ------------------------------------------------------------------------------
>>              |            Delta-method
>>              |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>>          _at |
>>           1  |   1.828415    .042767    42.75   0.000     1.744593    1.912237
>>           2  |    1.74101    .029594    58.83   0.000     1.683007    1.799013
>>           3  |    1.99406   .0351737    56.69   0.000     1.925121    2.062999
>>           4  |   1.906655   .0277658    68.67   0.000     1.852235    1.961075
>>           5  |   2.159704   .0286555    75.37   0.000     2.103541    2.215868
>>           6  |   2.072299   .0290146    71.42   0.000     2.015432    2.129167
>>           7  |   2.325349   .0241011    96.48   0.000     2.278112    2.372586
>>           8  |   2.237944   .0329929    67.83   0.000     2.173279    2.302609
>>           9  |   2.490994   .0227236   109.62   0.000     2.446456    2.535531
>>          10  |   2.403589   .0388715    61.83   0.000     2.327402    2.479775
>>          11  |   2.656638   .0250527   106.04   0.000     2.607536    2.705741
>>          12  |   2.569233   .0459263    55.94   0.000     2.479219    2.659247
>> ------------------------------------------------------------------------------
>>
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