help for cpoisson                                                (Joseph Hilbe)

Censored Poisson regression: survival parameterization

cpoisson depvar [varlist] [if exp] [in range] , censor(varname) [ offset(varname) exposure(varname) cluster(varname) level(#) from(asis) irr robust nolog maximize_options survey_options]

Note: the option censor must 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, and pweights are allowed; see help weights.

cpoisson provides access to all maximize options; see help maximize.

cpoisson provides access to all survey options; see help svy.


cpoisson fits a censored Poisson maximum-likelihood regression of depvar on indepvars, where depvar is 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 would poisson.

cpoisson acccepts all of the help maximize options, the constraint() 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 lf method.


+-------+ ----+ 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 a varname in model with coefficient constrained to 1.

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

constraints(constraints) apply specified linear constraints.

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


robust specifies that the Huber/White/sandwich estimator of variance is to be used in place of the traditional calculation. robust combined with cluster() allows observations which are not independent within cluster (although they must be independent between clusters). If you specify pweights, robust is implied.

vce(options) allowed. vce() supports robust, opg, and native. vce does not support options bootstrap or jacknife, However, cpoisson does support the bootstrap and jacknife commands, so these modeling capabilities are allowed.

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

nolog suppresses 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_options are all available. See help svy

Author and support

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


cpoisson is a user authored program. Support is by author. See Hardin & Hilbe, Generalized Linear Models and Extensions, Stata Press for discussion. Related information can also be obtained at [R] poisson.

Examples Before 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 see

Manual: [R] Poisson regression; [SVY] Svy: poisson

Online: help cpoisson poisson