= Stata estat =

'''`estat`''' is a post-estimation command.

<<TableOfContents>>

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== Usage ==



=== Vce ===



=== Gof ===

To calculate goodness of fit for a model, try:

{{{
. use https://www.stata-press.com/data/r18/lbw
(Hosmer & Lemeshow data)

. logistic low age lwt i.race smoke ptl ht ui

Logistic regression                                     Number of obs =    189
                                                        LR chi2(8)    =  33.22
                                                        Prob > chi2   = 0.0001
Log likelihood = -100.724                               Pseudo R2     = 0.1416

------------------------------------------------------------------------------
         low | Odds ratio   Std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         age |   .9732636   .0354759    -0.74   0.457     .9061578    1.045339
         lwt |   .9849634   .0068217    -2.19   0.029     .9716834    .9984249
             |
        race |
      Black  |   3.534767   1.860737     2.40   0.016     1.259736    9.918406
      Other  |   2.368079   1.039949     1.96   0.050     1.001356    5.600207
             |
       smoke |   2.517698    1.00916     2.30   0.021     1.147676    5.523162
         ptl |   1.719161   .5952579     1.56   0.118     .8721455    3.388787
          ht |   6.249602   4.322408     2.65   0.008     1.611152    24.24199
          ui |     2.1351   .9808153     1.65   0.099     .8677528      5.2534
       _cons |   1.586014   1.910496     0.38   0.702     .1496092     16.8134
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.

. estat gof

Goodness-of-fit test after logistic model
Variable: low

      Number of observations =    189
Number of covariate patterns =    182
           Pearson chi2(173) = 179.24
                 Prob > chi2 = 0.3567
}}}

The [[Statistics/PearsonChiSquaredTest|Pearson chi-squared test]] is not significant, so the model is not rejected. However, when the number of covariate patterns approaches the number of observations, the Pearson chi-squared test is not necessarily applicable.

Using the '''group''' option, dividing the observations into n-tiles, is a possible solution.

{{{
. estat gof, group(10)
note: obs collapsed on 10 quantiles of estimated probabilities.

Goodness-of-fit test after logistic model
Variable: low

 Number of observations =    189
       Number of groups =     10
Hosmer–Lemeshow chi2(8) =   9.65
            Prob > chi2 = 0.2904
}}}

The [[Statistics/HosmerLemeshowTest|Hosmer-Lemeshow test]] also is not significant, so the model is still not rejected. However, it should be noted that the Hosmer-Lemeshow test is not stable to n-tiles thresholds.

The `gof` subcommand is compatible with [[Stata/Svy|survey data]].

{{{
. use https://www.stata-press.com/data/r18/nhanes2d

. svy: logistic highbp height weight age female
[snip]

. estat gof

Logistic model for highbp, goodness-of-fit test

                      F(9,23) =         5.32
                     Prob > F =         0.0006
}}}

The F-statistic is significant, so the model is not a good fit.



=== Classification ===

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== See also ==

[[https://www.stata.com/manuals/restat.pdf|Stata manual for estat]]

[[https://www.stata.com/manuals/restatvce.pdf|Stata manual for estat vce]]

[[https://www.stata.com/manuals/restatgof.pdf|Stata manual for estat gof]] (this page specifically for [[Stata/Logistic|logitic]], [[Stata/Logit|logit]], or [[Stata/Probit|probit]] models)

[[https://www.stata.com/manuals/restatclassification.pdf|Stata manual for estat classification]]



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CategoryRicottone