## Stata 15 help for slogit_postestimation

```
[R] slogit postestimation -- Postestimation tools for slogit

Postestimation commands

The following postestimation commands are available after slogit:

Command            Description
-------------------------------------------------------------------------
contrast         contrasts and ANOVA-style joint tests of estimates
estat ic         Akaike's and Schwarz's Bayesian information criteria
(AIC and BIC)
estat summarize  summary statistics for the estimation sample
estat vce        variance-covariance matrix of the estimators (VCE)
estat (svy)      postestimation statistics for survey data
* hausman          Hausman's specification test
lincom           point estimates, standard errors, testing, and
inference for linear combinations of coefficients
* lrtest           likelihood-ratio test
margins          marginal means, predictive margins, marginal effects,
and average marginal effects
marginsplot      graph the results from margins (profile plots,
interaction plots, etc.)
nlcom            point estimates, standard errors, testing, and
inference for nonlinear combinations of coefficients
predict          predicted probabilities, estimated index and its
approximate standard error
predictnl        point estimates, standard errors, testing, and
inference for generalized predictions
pwcompare        pairwise comparisons of estimates
suest            seemingly unrelated estimation
test             Wald tests of simple and composite linear hypotheses
testnl           Wald tests of nonlinear hypotheses
-------------------------------------------------------------------------
* hausman and lrtest are not appropriate with svy estimation results.

Syntax for predict

predict [type] {stub* | newvar | newvarlist} [if] [in] [, statistic
outcome(outcome)]

predict [type] {stub* | newvarlist} [if] [in] , scores

statistic          Description
-------------------------------------------------------------------------
Main
pr               probability of one of or all the dependent variable
outcomes; the default
xb               index for the kth outcome
stdp             standard error of the index for the kth outcome
-------------------------------------------------------------------------
If you do not specify outcome(), pr (with one new variable specified),
xb, and stdp assume outcome(#1).
You specify one or k new variables with pr, where k is the number of
outcomes.
You specify one new variable with xb and stdp.
These statistics are available both in and out of sample; type predict
... if e(sample) ... if wanted only for the estimation sample.

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as
probabilities, indexes for the kth outcome, and standard errors.

Options for predict

+------+
----+ Main +-------------------------------------------------------------

pr, the default, calculates the probability of each of the categories of
the dependent variable or the probability of the level specified in
outcome().  If you specify the outcome(outcome) option, you need to
specify only one new variable; otherwise, you must specify a new
variable for each category of the dependent variable.

xb calculates the index for outcome level k and dimension d.  It returns
a vector of zeros if k = e(i_base).  A synonym for xb is index.  If
outcome() is not specified, outcome(#1) is assumed.

stdp calculates the standard error of the index.  A synonym for stdp is
seindex.  If outcome() is not specified, outcome(#1) is assumed.

outcome(outcome) specifies the outcome for which the statistic is to be
calculated.  equation() is a synonym for outcome(): it does not
matter which you use.  outcome() or equation() can be specified using

#1, #2, ..., where #1 means the first category of the dependent
variable, #2 means the second category, etc.;

the values of the dependent variable; or

the value labels of the dependent variable if they exist.

scores calculates the equation-level score variables.  For models with d
dimensions and m levels, d + (d + 1)(m - 1) new variables are
created.

The first d new variables will contain the scores for the d
regression equations.

The next d(m - 1) new variables will contain the scores for the scale
parameters.

The last m - 1 new variables will contain scores for the intercepts.

Syntax for margins

margins [marginlist] [, options]

margins [marginlist] , predict(statistic ...) [predict(statistic ...)
...] [options]

statistic          Description
-------------------------------------------------------------------------
default            probabilities for each outcome
pr                 probability of one of or all the dependent variable
outcomes
xb                 index for the kth outcome
stdp               not allowed with margins
-------------------------------------------------------------------------
pr and xb default to the first outcome.

Statistics not allowed with margins are functions of stochastic
quantities other than e(b).

For the full syntax, see [R] margins.

Statistics > Postestimation

Description for margins

margins estimates margins of response for probabilities and indexes for
the kth outcome.

Example

Setup
. webuse sysdsn1

Fit stereotype logistic regression model
. slogit insure age male nonwhite i.site, dim(1) base(1)

Estimate group probabilities
. predict pIndemnity pPrepaid pUninsure

```