Stata 15 help for heckprobit_postestimation

[R] heckprobit postestimation -- Postestimation tools for heckprobit

Postestimation commands

The following postestimation commands are available after heckprobit:

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 estimates cataloging estimation results * 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 predictions, residuals, influence statistics, and other diagnostic measures 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] newvar [if] [in] [, statistic nooffset ]

predict [type] {stub*|newvar_reg newvar_sel newvar_athrho} [if] [in], scores

statistic Description ------------------------------------------------------------------------- Main pmargin Pr(depvar=1); the default p11 Pr(depvar=1, depvar_s=1) p10 Pr(depvar=1, depvar_s=0) p01 Pr(depvar=0, depvar_s=1) p00 Pr(depvar=0, depvar_s=0) psel Pr(depvar_s=1) pcond Pr(depvar=1 | depvar_s=1) xb linear prediction stdp standard error of the linear prediction xbsel linear prediction for selection equation stdpsel standard error of the linear prediction for selection equation -------------------------------------------------------------------------

These statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only for the estimation sample.

Menu for predict

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as probabilities, linear predictions, and standard errors.

Options for predict

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

pmargin, the default, calculates the univariate (marginal) predicted probability of success Pr(depvar=1).

p11 calculates the bivariate predicted probability Pr(depvar=1, depvar_s=1).

p10 calculates the bivariate predicted probability Pr(depvar=1, depvar_s=0).

p01 calculates the bivariate predicted probability Pr(depvar=0, depvar_s=1).

p00 calculates the bivariate predicted probability Pr(depvar=0, depvar_s=0).

psel calculates the univariate (marginal) predicted probability of selection Pr(depvar_s=1).

pcond calculates the conditional (on selection) predicted probability of success Pr(depvar=1 | depvar_s=1) = Pr(depvar=1, depvar_s=1)/Pr(depvar_s=1).

xb calculates the probit linear prediction.

stdp calculates the standard error of the prediction, which can be thought of as the standard error of the predicted expected value or mean for the observation's covariate pattern. The standard error of the prediction is also referred to as the standard error of the fitted value.

xbsel calculates the linear prediction for the selection equation.

stdpsel calculates the standard error of the linear prediction for the selection equation.

nooffset is relevant only if you specified offset(varname) for heckprobit. It modifies the calculations made by predict so that they ignore the offset variable; the linear prediction is treated as xb rather than xb + offset.

scores calculates equation-level score variables.

The first new variable will contain the derivative of the log likelihood with respect to the regression equation.

The second new variable will contain the derivative of the log likelihood with respect to the selection equation.

The third new variable will contain the derivative of the log likelihood with respect to the third equation (athrho).

Syntax for margins

margins [marginlist] [, options]

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

statistic Description ------------------------------------------------------------------------- pmargin Pr(depvar=1); the default p11 Pr(depvar=1, depvar_s=1) p10 Pr(depvar=1, depvar_s=0) p01 Pr(depvar=0, depvar_s=1) p00 Pr(depvar=0, depvar_s=0) psel Pr(depvar_s=1) pcond Pr(depvar=1 | depvar_s=1) xb linear prediction xbsel linear prediction for selection equation stdp not allowed with margins stdpsel not allowed with margins -------------------------------------------------------------------------

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

For the full syntax, see [R] margins.

Menu for margins

Statistics > Postestimation

Description for margins

margins estimates margins of response for probabilities and linear predictions.

Examples

Setup . webuse school

Fit probit model with sample selection . heckprobit private years logptax, sel(vote=years loginc logptax)

Estimate marginal probability that private equals one . predict pmarg

Compare to probit model with an if qualifier . probit private years if vote==1

Calculated predicted probabilities . predict phat


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