help ztnb postestimation dialog: predict
also see: ztnb
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Title
[R] ztnb postestimation -- Postestimation tools for ztnb
Description
The following postestimation commands are available for ztnb:
command description
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estat AIC, BIC, VCE, and estimation sample summary
estat (svy) postestimation statistics for survey data
estimates cataloging estimation results
lincom point estimates, standard errors, testing, and inference
for linear combinations of coefficients
(1) lrtest likelihood-ratio test
margins marginal means, predictive margins, marginal effects,
and average marginal effects
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
suest seemingly unrelated estimation
test Wald tests of simple and composite linear hypotheses
testnl Wald tests of nonlinear hypotheses
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(1) lrtest is not appropriate with svy estimation results.
Syntax for predict
predict [type] newvar [if] [in] [, statistic nooffset]
predict [type] {stub*|newvar_reg newvar_disp} [if] [in] , scores
statistic description
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Main
n number of events; the default
ir incidence rate
cm estimate of the conditional mean, E(y_j|y_j > 0)
xb linear prediction
stdp standard error of the linear prediction
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These statistics are available both in and out of sample; type predict
... if e(sample) ... if wanted only for the estimation sample.
Menu
Statistics > Postestimation > Predictions, residuals, etc.
Options for predict
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----+ Main +-------------------------------------------------------------
n, the default, calculates the predicted number of events, which is
exp(xb) if neither offset() nor exposure() was specified when the
model was fit; exp(xb + offset) if offset() was specified; or
exp(xb)*exposure if exposure() was specified.
ir calculates the incidence rate exp(xb), which is the predicted number
of events when exposure is 1. This is equivalent to specifying both
n and nooffset options.
cm calculates the estimate of the conditional mean of n, given n>0, i.e.,
E(n|n > 0), which is exp(xb)/P(n > 0|x) if neither offset() nor
exposure() was specified when the zero-truncated negative binomial
model was fit, or exp(xb + offset)/P( n > 0|x) if offset() was
specified, or exp(xb)/P(n > 0|x)*exposure if exposure() was
specified.
xb calculates the linear prediction, which is xb if neither offset() nor
exposure() was specified; xb + offset if offset() was specified; or
xb + ln(exposure) if exposure() was specified; see nooffset below.
stdp calculates the standard error of the linear prediction.
nooffset is relevant only if you specified offset() or exposure() when
you fit the model. It modifies the calculations made by predict so
that they ignore the offset or exposure variable; the linear
prediction is treated as xb rather than as xb + offset or
xb + ln(exposure). Specifying predict ..., nooffset is equivalent to
specifying predict ..., ir.
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 dispersion equation.
Examples
Setup
. webuse rod93
Fit zero-truncated negative binomial regression model
. ztnb deaths i.cohort, exposure(exposure)
Predict incidence rate of death
. predict incidence, ir
Predict the number of events
. predict nevents, n
Predict the number of events, conditional on the number being positive
. predict condmean, cm
Also see
Manual: [R] ztnb postestimation
Help: [R] ztnb
