help for cpoissone (Joseph Hilbe)

Censored Poisson regression: econometric

cpoissone depvar [varlist]
[if exp] [in range] ,
censor(varname) CLEft() CRIght()
[ 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 = not censored, 1 = left censored,
-1 = right censored.

Note: Type value of left censor site in cleft().

Type value of right censor site in cright().

aweights, fweights, iweights, and pweights are
allowed; see help weights.

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

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

Description

cpoissone 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.

Values on either side of the site of censoring are revalued to the
value of the censor value.

cpoissone accepts 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.

Options

Model

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

cleft(#) for left censor site; cright(#) for right censor site

censor(1) and no cleft or cright values declared is a standard Poisson model

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

cluster(varname)

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

Remarks

cpoissone is a user authored program. Support is by author. See Hilbe,
Negative Binomial Regression, Cambridge University Press, for discussion. Related
information can also be obtained at [R] poisson. Or see cpoisson

Examples

. cpoissone time hmo age, censor(cenvcar) cle(3) nolog irr

. cpoissone time hmo age, censor(cenvar) cleft(2) cright(30) nolog cluster(provnum)

. bootstrap: cpoissone deaths smokes a2-a5, censor(cenvar) cright(10) exposure(pyears) irr nolog

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

. svy: cpoissone zinc age age2 weight female black orace rural, censor(cv) cright(20) nolog irr

Also see

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

Online: help cpoisson poisson