Stata estat

estat is a post-estimation command.


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 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 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 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


See also

Stata manual for estat

Stata manual for estat vce

Stata manual for estat gof (this page specifically for logitic, logit, or probit models)

Stata manual for estat classification


CategoryRicottone

Stata/Estat (last edited 2025-04-04 03:19:02 by DominicRicottone)