## Stata 15 help for mprobit_postestimation

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

Postestimation commands

The following postestimation commands are available after mprobit:

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
* forecast         dynamic forecasts and simulations
* 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, linear predictions, and
standard errors
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
-------------------------------------------------------------------------
* forecast, hausman, and lrtest are not appropriate with svy estimation
results.  forecast is also not appropriate with mi 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               predicted probabilities; the default
xb               linear prediction
stdp             standard error of the linear prediction
-------------------------------------------------------------------------
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, linear predictions, and standard errors.

Options for predict

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

pr, the default, calculates the predicted probabilities.  If you do not
also specify the outcome() option, you specify k new variables, where
k is the number of categories of the dependent variable.  Say that
you fit a model by typing mprobit result x1 x2, and result takes on
three values.  Then you could type predict p1 p2 p3 to obtain all
three predicted probabilities.  If you specify the outcome() option,
you must specify one new variable.  Say that result takes on the
values 1, 2, and 3.  Typing predict p1, outcome(1) would produce the
same p1.

xb calculates the linear prediction, x_i a_j, for alternative j and
individual i.  The index, j, corresponds to the outcome specified in
outcome().

stdp calculates the standard error of the linear prediction.

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.  The jth new
variable will contain the scores for the jth fitted equation.

Syntax for margins

margins [marginlist] [, options]

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

statistic          Description
-------------------------------------------------------------------------
default            probabilities for each outcome
pr                 probability for a specified outcome
xb                 linear prediction for a specified 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 linear
predictions.

Examples

Setup
. webuse sysdsn1
. mprobit insure age male nonwhite i.site

Test that the coefficients on 2.site and 3.site are 0 in all equations
. test 2.site 3.site

Test that all coefficients in equation Uninsure are 0
. test [Uninsure]

Test that 2.site and 3.site are jointly 0 in the Prepaid equation
. test [Prepaid]: 2.site 3.site

Test that coefficients in equations Prepaid and Uninsure are equal
. test [Prepaid=Uninsure]

Predict probability that a person belongs to the Prepaid insurance
category
. predict p1 if e(sample), outcome(2)

```