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= Stata Logistic = = Stata logistic =
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The '''`logistic`''' command runs a logistic regression.

Compare to the [[Stata/Logit|logit]] command, which only shows the odds ratios if the `or` option is specified, while `logistic` to always shows those.		 The '''`logistic`''' command fits a [[Statistics/LogisticModel|logistic model]].
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Adapted from [[https://stats.idre.ucla.edu/stata/dae/logistic-regression/|here]]:
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logistic dependent independent . use https://stats.idre.ucla.edu/stat/stata/dae/binary, clear

. logistic admit gre gpa i.rank

Logistic regression Number of obs = 400
                                                  LR chi2(5) = 41.46
                                                  Prob > chi2 = 0.0000
Log likelihood = -229.25875 Pseudo R2 = 0.0829

------------------------------------------------------------------------------
       admit | Odds ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
         gre | 1.002267 .0010965 2.07 0.038 1.00012 1.004418
         gpa | 2.234545 .7414652 2.42 0.015 1.166122 4.281877
             |
        rank |
          2 | .5089309 .1610714 -2.13 0.033 .2736922 .9463578
          3 | .2617923 .0903986 -3.88 0.000 .1330551 .5150889
          4 | .2119375 .0885542 -3.71 0.000 .0934435 .4806919
             |
       _cons | .0185001 .0210892 -3.50 0.000 .0019808 .1727834
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.
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Compare the output of [[Stata/Logit|logit]], which ordinarily shows coefficients rather than odds ratios.
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[[https://www.stata.com/manuals/rlogistic.pdf|Stata manual for logistic]]

Stata logistic

The logistic command fits a logistic model.

Contents

  1. Stata logistic
    1. Usage
    2. See also

Usage

Adapted from here: 

. use https://stats.idre.ucla.edu/stat/stata/dae/binary, clear

. logistic admit gre gpa i.rank

Logistic regression                               Number of obs   =        400
                                                  LR chi2(5)      =      41.46
                                                  Prob > chi2     =     0.0000
Log likelihood = -229.25875                       Pseudo R2       =     0.0829

------------------------------------------------------------------------------
       admit | Odds ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         gre |   1.002267   .0010965     2.07   0.038      1.00012    1.004418
         gpa |   2.234545   .7414652     2.42   0.015     1.166122    4.281877
             |
        rank |
          2  |   .5089309   .1610714    -2.13   0.033     .2736922    .9463578
          3  |   .2617923   .0903986    -3.88   0.000     .1330551    .5150889
          4  |   .2119375   .0885542    -3.71   0.000     .0934435    .4806919
             |
       _cons |   .0185001   .0210892    -3.50   0.000     .0019808    .1727834
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.

Compare the output of logit, which ordinarily shows coefficients rather than odds ratios.

See here for details on factor variables.

See also

Stata manual for logistic

Stata manual for logistic post-estimation

CategoryRicottone

Stata/Logistic (last edited 2025-04-04 00:28:02 by DominicRicottone)