------------------------------------------------------------------------------- help forcpoisson(Joseph Hilbe) -------------------------------------------------------------------------------

Censored Poisson regression: survival parameterization

cpoissondepvar[varlist] [ifexp] [inrange],censor(varname)[offset(varname)exposure(varname)cluster(varname)level(#)from(asis)irrrobustnologmaximize_optionssurvey_options]Note: the option

censormust be included in the command. A censor variable must use the following numbers to indicate the type of censoring: 0 =left censored, 1 =not censored, -1 =right censored.

aweights,fweights,iweights, andpweights are allowed; see help weights.

cpoissonprovides access to allmaximizeoptions; see help maximize.

cpoissonprovides access to allsurveyoptions; see help svy.

Description

cpoissonfits a censored Poisson maximum-likelihood regression ofdepvaronindepvars, wheredepvaris a non-negative count variable. The censor option is required. If no observations are censored, a censor variable with all 1's must be specified. Interpret parameter estimates as one wouldpoisson.

cpoissonacccepts all of thehelp maximizeoptions, theconstraint()option, and all survey options and capabilities documented in[SVY]; including multi-level surveys; poststratification; and BRR, jackknife, and linearization VCE estimators.This program uses

ml lfmethod.

Options+-------+ ----+ Model +------------------------------------------------------------

censor(cenvar)is required. Values of 1 indicate a non-censored, 0 a left censored, and -1 a right censored observation.

offset(varname)specifies avarnamein model with coefficient constrained to 1.

exposure(varname)specifies aln(varname)in model with coefficient constrained to 1.

constraints(constraints)apply specified linear constraints.

+-----------+ ----+ SE/Robust +--------------------------------------------------------

cluster(varname)

robustspecifies that the Huber/White/sandwich estimator of variance is to be used in place of the traditional calculation.robustcombined withcluster()allows observations which are not independent within cluster (although they must be independent between clusters). If you specifypweights,robustis implied.

vce(options)allowed.vce()supportsrobust,opg, andnative.vcedoes not support optionsbootstraporjacknife, However,cpoissondoes support thebootstrapandjacknifecommands, so these modeling capabilities are allowed.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#)specifies the confidence level, in percent, for confidence intervals of the coefficients; see help level.

nologsuppresses the iteration log.

+-------------+ ----+ max options +------------------------------------------------------

maximize_options: technique(algorithm_spec), [no]log, trace, hessian, gradient, showstep, shownrtolerance, difficult, iterate(#), tolerance(#), ltolerance(#), gtolerance(#), nrtolerance(#), nonrtolerance, from(init_specs); see maximize.

+-------------+ ----+ svy options +------------------------------------------------------

survey_optionsare all available. See help svy

Author and support

Joseph Hilbe,Arizona State University:hilbe@asu.edu

Remarks

cpoissonis a user authored program. Support is by author. SeeHardin &Hilbe,Generalized Linear Models and Extensions,Stata Pressfor discussion. Related information can also be obtained at[R] poisson.

ExamplesBefore examples 1. gen byte cenvar = 1

Before example 2. replace cenvar = 0 if time<=3. replace cencar = -1 if time>=50

. cpoisson time hmo age, censor(cenvar) nolog irr

. cpoisson time hmo age, censor(cenvar) nolog cluster(provnum)

. bootstrap: cpoisson deaths smokes a2-a5, censor(cenvar)exposure(pyears) irr nolog

. svyset psuid [pweight=finalwgt], strata(stratid)

. svy: cpoisson zinc age age2 weight female black orace rural, censor(cv)nolog irr

Also seeManual:

[R] Poisson regression;[SVY] Svy: poissonOnline:

helpcpoissonpoisson