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The '''`logit`''' command runs a logistic regression. Compare to the [[Stata/Logistic|logistic]] command, which always shows the odds ratios, while the `or` option must be specified on `logit` to show those. |
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| This example is per [[https://stats.idre.ucla.edu/stata/dae/logistic-regression/|UCLA: Statistical Consulting Group]]: |
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| logit dependent independent | . logit admit gre gpa i.rank Iteration 0: log likelihood = -249.98826 Iteration 1: log likelihood = -229.66446 Iteration 2: log likelihood = -229.25955 Iteration 3: log likelihood = -229.25875 Iteration 4: log likelihood = -229.25875 Logistic regression Number of obs = 400 LR chi2(5) = 41.46 Prob > chi2 = 0.0000 Log likelihood = -229.25875 Pseudo R2 = 0.0829 ------------------------------------------------------------------------------ admit | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- gre | .0022644 .001094 2.07 0.038 .0001202 .0044086 gpa | .8040377 .3318193 2.42 0.015 .1536838 1.454392 | rank | 2 | -.6754429 .3164897 -2.13 0.033 -1.295751 -.0551346 3 | -1.340204 .3453064 -3.88 0.000 -2.016992 -.6634158 4 | -1.551464 .4178316 -3.71 0.000 -2.370399 -.7325287 | _cons | -3.989979 1.139951 -3.50 0.000 -6.224242 -1.755717 ------------------------------------------------------------------------------ |
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---- == Estimates == The estimates can be accessed through any of the following commands... * `predict` creates a variable storing the predicted probability for each case * `margins` displays the marginal predicted probabilities |
Stata Logit
The logit command runs a logistic regression.
Compare to the logistic command, which always shows the odds ratios, while the or option must be specified on logit to show those.
Contents
Usage
This example is per UCLA: Statistical Consulting Group:
. logit admit gre gpa i.rank
Iteration 0: log likelihood = -249.98826
Iteration 1: log likelihood = -229.66446
Iteration 2: log likelihood = -229.25955
Iteration 3: log likelihood = -229.25875
Iteration 4: log likelihood = -229.25875
Logistic regression Number of obs = 400
LR chi2(5) = 41.46
Prob > chi2 = 0.0000
Log likelihood = -229.25875 Pseudo R2 = 0.0829
------------------------------------------------------------------------------
admit | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
gre | .0022644 .001094 2.07 0.038 .0001202 .0044086
gpa | .8040377 .3318193 2.42 0.015 .1536838 1.454392
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rank |
2 | -.6754429 .3164897 -2.13 0.033 -1.295751 -.0551346
3 | -1.340204 .3453064 -3.88 0.000 -2.016992 -.6634158
4 | -1.551464 .4178316 -3.71 0.000 -2.370399 -.7325287
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_cons | -3.989979 1.139951 -3.50 0.000 -6.224242 -1.755717
------------------------------------------------------------------------------See here for details on factor variables.
Estimates
The estimates can be accessed through any of the following commands...
predict creates a variable storing the predicted probability for each case
margins displays the marginal predicted probabilities
See also
Stata manual for logit post-estimation