help for tpoisson (Joseph Hilbe)

Truncated Poisson regression

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

Note: the option trunc must be included in the command. A trunc variable must
use the following numbers to indicate the type of truncation: 0 = left truncated, 1 = not truncated,
-1 = right truncated.

Note: Type value of left truncated site in tleft().

Type value of right truncated site in tright().

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

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

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

Description

tpoisson fits a truncated Poisson maximum-likelihood regression
of depvar on indepvars, where depvar is a non-negative count variable.
The trunc option is required. If no observations are truncated, a trunc variable
with all 1's must be specified. Interpret parameter estimates as one would poisson.

Values on either side of the site of truncation are revalued to the
value of the trunc value.

tpoisson 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

trunc(truncvar) is required. Values of 1 indicate a non-truncated, 0 a left
truncated, and -1 a right truncated observation. truncvar may be numeric or a variable.

tleft(#) for left truncation site; tright(#) for right truncation site

trunc(1) and no tleft or tright 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, tpoisson 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

tpoisson 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 or cpoissone

Examples

Before example 1
. gen byte truncvar = 1
. replace truncvar = 0 if time<=3

. tpoisson time hmo age, trunc(truncvar) tle(3) nolog irr

Before example 2
. replace truncvar = 1
. replace truncvar = 0 if time<=2
. replace truncvar = -1 if time >=30

. tpoisson time hmo age, trunc(truncvar) tleft(2) tright(30) nolog cluster(provnum)

. bootstrap: tpoisson deaths smokes a2-a5, trunc(truncvar) tright(10) exposure(pyears) irr nolog

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

. svy: tpoisson zinc age age2 weight female black orace rural, trunc(cv) tright(20) nolog irr

Also see

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

Online: help cpoisson cpoissone poisson