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Re: st: svy, subpop ( ) with version 10


From   "Leda Inga" <ledainga@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: svy, subpop ( ) with version 10
Date   Fri, 6 Jun 2008 21:46:02 -0500

Unfortunately I don't have cluster specific variables. I'm worried
that you say fixed-effects logit will not solve the problem. I've read
the reference manual and it says that clogit ( which is the same as fe
logit) can be used for matched-case controles studies. In my data
every individual in a certain cluster for which the dependet variable
is zero would be a control for the rest (for which the dependent is
one). It also says that it doesn't matter if each cluster has a
different number of observations.

Finally, in the book of Wooldridge of panel data (p 496) it says that
an unobserved effect framework can be used  for cluster samples. The
author cites the work of Geronimus and Korenman (1992) where they "use
sister pairs to determine the effects of teenage motherhood on
subsequente economic outcomes". They use a fixed-effects approach when
the outcome is binary.
In my model the most important omitted variables correlated with the
regressors are geographical access and cultural barriers.

Please, I would like to be confirmed if my approach is really incorrect.

2008/6/6 Steven Samuels <sjhsamuels@earthlink.net>:
> If you want a 3-level or higher model with estimated variances at each
> level, then your only recourse is -gllamm-. You would have to compute your
> own weighted predictions.
>
> In any case, -xtlogit- will not solve your problem; its  "fixed-effects"
> option  makes sense only for longitudinal data.
>
>  -svylogit- will give you the standard goodness of fit statistics; will
> permit you to model multiple stages of sampling, but will not provide
> estimators of variance for each level. You can include cluster-specific
> covariates and  test the interaction of cluster-covariates and individual
> covariates.
>
> -Steven
> On Jun 6, 2008, at 9:29 PM, Leda Inga wrote:
>
>> I'm still trying to find if there's a good measure of fit for a
>> fixed-effect logit model. As I answered in the last email, I'm really
>> interesed in getting one.
>>
>> 2008/6/6 Steven Samuels <sjhsamuels@earthlink.net>:
>>>
>>> The numbers of PSU and strata (before subsetting) are different.
>>> Therefore
>>> either the -svyset- commands or the data sets differ.  By the way, how
>>> did
>>> you resolve your cluster problem?
>>>
>>> Steven
>>> On Jun 6, 2008, at 8:04 PM, Leda Inga wrote:
>>>
>>>> Hi,
>>>>
>>>> I'm running a logit using svy and found a difference in the
>>>> coefficients and pvalues reported by version 9 and 10 of Stata. I
>>>> thought that it could be because of the observations that each one
>>>> takes into account. As you can see below the version 10 considers 4178
>>>> observations but  there are actually 8471 and the results are the same
>>>> as using the "if" after svy. Can anybody explain this?
>>>>
>>>> The command I used for both versions was:
>>>>
>>>> svy, subpop(urbano): logit PS n_hijos educ seguro V157 NSE rural
>>>> _ISREGION_3 _ISREGION_5 CPci CPci2 labor_prol
>>>>
>>>> VERSION 10:
>>>>
>>>> Survey: Logistic regression
>>>>
>>>> Number of strata   =        24                  Number of obs      =
>>>>  4178
>>>> Number of PSUs   =       451                 Population size    =
>>>> 2920.9792
>>>>
>>>>                           Subpop. no. of obs =      4178
>>>>                                                         Subpop. size
>>>>     = 2920.9792
>>>>                                                         Design df
>>>>     =       427
>>>>                                                         F(  10,
>>>> 418)    =     30.43
>>>>                                                         Prob > F
>>>>     =    0.0000
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>>            |             Linearized
>>>>         PS |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
>>>> Interval]
>>>>
>>>>
>>>> -------------+----------------------------------------------------------------
>>>>    n_hijos |  -.0627022   .0233953    -2.68   0.008    -.1086865
>>>> -.0167179
>>>>       educ |   .0995025   .0176722     5.63   0.000     .0647671
>>>>  .1342379
>>>>     seguro |   .2691795   .1430446     1.88   0.061    -.0119797
>>>>  .5503387
>>>>       V157 |   .2184025   .0961237     2.27   0.024     .0294679
>>>>  .4073371
>>>>        NSE |   .5893834   .0859681     6.86   0.000     .4204101
>>>>  .7583568
>>>> _ISREGION_3 |  -.8503491   .2073588    -4.10   0.000     -1.25792
>>>> -.4427781
>>>> _ISREGION_5 |  -.7629466   .2529318    -3.02   0.003    -1.260093
>>>> -.2658003
>>>>       CPci |    .298412   .0547975     5.45   0.000     .1907057
>>>>  .4061184
>>>>      CPci2 |  -.0109094   .0043379    -2.51   0.012    -.0194356
>>>> -.0023832
>>>>  labor_prol |    .415821   .1035528     4.02   0.000     .2122843
>>>>  .6193578
>>>>      _cons |  -2.961981   .3026012    -9.79   0.000    -3.556754
>>>> -2.367207
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Note: 25 strata omitted because they contain no subpopulation members.
>>>>
>>>>
>>>> VERSION 9:
>>>>
>>>> Survey: Logistic regression
>>>>
>>>> Number of strata   =        49                  Number of obs      =
>>>>  8471
>>>> Number of PSUs   =      1118                 Population size    =
>>>>  6948.092
>>>>                                                         Subpop. no.
>>>> of obs =      4212
>>>>                                                         Subpop. size
>>>>     = 2945.3116
>>>>                                                         Design df
>>>>     =      1069
>>>>                                                         F(  10,
>>>> 1060)    =     31.19
>>>>                                                         Prob > F
>>>>     =    0.0000
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>>            |             Linearized
>>>>         PS |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
>>>> Interval]
>>>>
>>>>
>>>> -------------+----------------------------------------------------------------
>>>>    n_hijos |  -.0624413    .023198    -2.69   0.007      -.10796
>>>> -.0169225
>>>>       educ |    .100353   .0178213     5.63   0.000     .0653842
>>>>  .1353218
>>>>     seguro |   .2789113   .1415214     1.97   0.049     .0012202
>>>>  .5566025
>>>>       V157 |   .2192173   .0962575     2.28   0.023     .0303421
>>>>  .4080924
>>>>        NSE |   .5896208   .0851999     6.92   0.000     .4224427
>>>>  .7567989
>>>> _ISREGION_3 |  -.8230625   .2058183    -4.00   0.000    -1.226916
>>>> -.4192088
>>>> _ISREGION_5 |  -.7412179   .2491071    -2.98   0.003    -1.230012
>>>> -.2524236
>>>>       CPci |   .2921813     .04976     5.87   0.000      .194543
>>>>  .3898195
>>>>      CPci2 |  -.0103967   .0037064    -2.81   0.005    -.0176694
>>>>  -.003124
>>>>  labor_prol |   .4267068   .1025795     4.16   0.000     .2254268
>>>>  .6279867
>>>>      _cons |   -2.97932    .293572   -10.15   0.000    -3.555362
>>>> -2.403277
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>>
>>>>
>>>> Thanks.
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