Stata 15 help for clogit_postestimation

[R] clogit postestimation -- Postestimation tools for clogit

Postestimation commands

The following standard postestimation commands are available after clogit:

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 linktest link test for model specification * 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]

statistic Description ------------------------------------------------------------------------- Main pc1 probability of a positive outcome; the default pu0 probability of a positive outcome, assuming fixed effect is zero xb linear prediction stdp standard error of the linear prediction * dbeta Delta-b influence statistic * dx2 Delta chi-squared lack-of-fit statistic * gdbeta Delta-b influence statistic for each group * gdx2 Delta chi-squared lack-of-fit statistic for each group * hat Hosmer and Lemeshow leverage * residuals Pearson residuals * rstandard standardized Pearson residuals score first derivative of the log likelihood with respect to xb ------------------------------------------------------------------------- Unstarred statistics are available both in and out of sample; type predict ... if e(sample) ... if wanted only for the estimation sample. Starred statistics are calculated only for the estimation sample, even when if e(sample) is not specified.

Starred statistics are available for multiple controls per case-matching design only. They are not available if vce(robust), vce(cluster clustvar), or pweights were specified with clogit.

dbeta, dx2, gdbeta, gdx2, hat, and rstandard are not available if constraints() was specified with clogit.

Menu for predict

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as probabilities, linear predictions, standard errors, influence statistics, lack-of-fit statistics, Hosmer and Lemeshow leverages, Pearson residuals, and equation-level scores.

Options for predict

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

pc1, the default, calculates the probability of a positive outcome conditional on one positive outcome within group.

pu0 calculates the probability of a positive outcome, assuming that the fixed effect is zero.

xb calculates the linear prediction.

stdp calculates the standard error of the linear prediction.

dbeta calculates the Delta-b influence statistic, a standardized measure of the difference in the coefficient vector that is due to deletion of the observation.

dx2 calculates the Delta chi-squared influence statistic, reflecting the decrease in the Pearson chi-squared that is due to deletion of the observation.

gdbeta calculates the approximation to the Pregibon stratum-specific Delta-b influence statistic, a standardized measure of the difference in the coefficient vector that is due to deletion of the entire stratum.

gdx2 calculates the approximation to the Pregibon stratum-specific Delta chi-squared influence statistic, reflecting the decrease in the Pearson chi-squared that is due to deletion of the entire stratum.

hat calculates the Hosmer and Lemeshow leverage or the diagonal element of the hat matrix.

residuals calculates the Pearson residuals.

rstandard calculates the standardized Pearson residuals.

score calculates the equation-level score, the derivative of the log likelihood with respect to the linear prediction.

nooffset is relevant only if you specified offset(varname) for clogit. It modifies the calculations made by predict so that they ignore the offset variable; the linear prediction is treated as xb rather than as xb + offset. This option cannot be specified with dbeta, dx2, gdbeta, gdx2, hat, and rstandard.

Syntax for margins

margins [marginlist] [, options]

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

statistic Description ------------------------------------------------------------------------- pu0 probability of a positive outcome, assuming fixed effect is zero; the default xb linear prediction pc1 not allowed with margins stdp not allowed with margins dbeta not allowed with margins dx2 not allowed with margins gdbeta not allowed with margins gdx2 not allowed with margins hat not allowed with margins residuals not allowed with margins rstandard not allowed with margins score 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 lowbirth2

Fit conditional logistic regression . clogit low lwt smoke ptd ht ui i.race, group(pairid)

Test that the coefficient on 2.race equals the coefficient on 3.race . test 2.race = 3.race

Predict the probability of a positive outcome conditional on one positive outcome within group . predict pc

Predict Hosmer and Lemeshow leverage . predict hat, hat


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