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


From   Steven Samuels <sjhsamuels@earthlink.net>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: svy, subpop ( ) with version 10
Date   Fri, 6 Jun 2008 22:07:20 -0400

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

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


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