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help for hpclg                                                   (Joseph Hilbe)
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Poisson-complementary log log hurdle regression

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

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

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

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

Description

hpclg fits a Poisson-cloglog maximum-likelihood hurdle model of depvar on indepvars, where depvar is a non-negative count variable.

hpclg 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.

Options

+-------+ ----+ 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, hpclg 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: jhilbe@aol.com

Remarks

hpclg is a user authored program. Support is by author. hpclg is one of a suite of hurdle programs created by the author. 2Oct2005

hpclg requires a response with counts including a number of 0's. irr for binary model.

Examples

. hpclg accident co_70_74 co_75_79 op_75_79, nolog exposure(service)

. hpclg accident co_70_74 co_75_79 op_75_79, nolog exposure(service) cluster(ship)

. bootstrap: hpclg accident co_70_74 co_75_79 op_75_79, nolog exposure(service)