zinb.hlp

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{smcl}
{* 22mar2005}{...}
{cmd:help zinb}{right:dialog:  {bf:{dialog zinb}}{space 15}}
{right:also see:  {help zinb postestimation}}
{hline}

{title:Title}

{p2colset 5 17 19 2}{...}
{p2col :{hi:[R] zinb} {hline 2}}Zero-inflated negative binomial 
regression{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 16 2}
{cmd:zinb} {depvar} [{indepvars}] {ifin} {weight}
{opt inf:late}{cmd:(}{varlist}[{cmd:,} {opth off:set(varname)}]|{cmd:_cons)}
[{it:{help zinb##zinb_options:options}}]

{marker zinb_options}{...}
{synoptset 28 tabbed}{...}
{synopthdr:options}
{synoptline}
{syntab:Model}
{p2coldent:* {opt inf:late()}}equation that determines whether the count is
zero{p_end}
{synopt :{opt nocon:stant}}suppress constant term{p_end}
{synopt :{opth exp:osure(varname:varname_e)}}include {opt ln(varname_e)} in model with
coefficient constrained to 1{p_end}
{synopt :{opth off:set(varname:varname_o)}}include {it:varname_o} in model with
coefficient constrained to 1{p_end}
{synopt :{cmdab:const:raints(}{it:{help estimation options##constraints():constraints}}{cmd:)}}apply specified linear constraints{p_end}
{synopt :{opt probit}}use probit model to characterize excess zeros;
default is logit{p_end}

{syntab:SE/Robust}
{synopt :{opth vce(vcetype)}}{it:vcetype} may be {opt oim}, {opt r:obust},
{opt opg}, {opt boot:strap}, or {opt jack:knife}{p_end}
{synopt :{opt r:obust}}synonym for {cmd:vce(robust)}{p_end}
{synopt :{opth cl:uster(varname)}}adjust standard errors for intragroup
correlation{p_end}

{syntab:Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is
{cmd:level(95)}.{p_end}
{synopt :{opt irr}}report incidence-rate rations{p_end}
{synopt :{opt vuong}}report Vuong test results{p_end}
{synopt :{opt zip}}perform zip likelihood-ratio test{p_end}

{syntab:Max options}
{synopt :{it:{help zinb##maximize_options:maximize_options}}}control maximization process; seldom
used{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}* {opt inf:late}{cmd:(}{it:varlist}[{cmd:,} {opt off:set(varname)}]|{cmd:_cons)} is required.{p_end}
{p 4 6 2}{cmd:bootstrap}, {cmd:by}, {cmd:jackknife}, {cmd:rolling},
{cmd:statsby}, and {cmd:xi} are allowed; see {help prefix}.{p_end}
{p 4 6 2}{cmd:fweight}s, {cmd:iweight}s, and {cmd:pweight}s are allowed; see
{help weight}.{p_end}
{p 4 6 2}See {help zinb postestimation} for additional capabilities of
estimation commands{p_end}


{title:Description}

{pstd}
{cmd:zinb} estimates a zero-inflated negative binomial regression of {depvar}
on {indepvars}, where {it:depvar} is a non-negative count variable.


{title:Options}

{dlgtab:Model}

{phang}
{cmd:inflate(}{varlist}[{cmd:,} {cmd:offset(}{varname}{cmd:)}]|{cmd:_cons)}
specifies the equation that determines whether the observed count is zero.
Conceptually, omitting {opt inflate()} would be equivalent to fitting the
model with {helpb nbreg}.

{pmore}
{cmd:inflate(}{varlist}[{cmd:, offset(}{varname}{cmd:)}]{cmd:)}
specifies the variables in the equation.  You may optionally include an offset
for this {varlist}.

{pmore}
{cmd:inflate(_cons)} specifies that the equation determining whether
the count is zero contains only an intercept.  To run a zero-inflated model of
{depvar} with only an intercept in both equations, type
{bind:{cmd:zinb} {it:depvar}{cmd:,} {cmd:inflate(_cons)}}.

{phang}
{opt noconstant}, {opt exposure(varname_e)}, {opt offset(varname_o)}, 
{opt constraints(constraints)}; see {help estimation options}. 

{phang}
{opt probit} specifies that a probit, instead of logit, model be
used to characterize the excess zeros in the data.

{dlgtab:SE/Robust}

{phang}
{opt vce(vcetype)}; see {it:{help vce_option}}.

{phang}
{opt robust}, {opth cluster(varname)}; see
   {help estimation options##robust:estimation options}.

{dlgtab:Reporting}

{phang}
{opt level(#)}; see {help estimation options##level():estimation options}. 

{phang}
{opt irr} reports estimated coefficients transformed to incidence-rate
ratios.  Standard errors and confidence intervals are similarly transformed.
This option affects how results are displayed, not how they are estimated or
stored.  {opt irr} may be specified at estimation or when replaying
previously estimated results.

{phang}
{opt vuong} specifies that the Vuong test of ZINB versus negative binomial be
reported.  This test statistic has a standard normal distribution with large
positive values favoring the ZINB model and large negative values
favoring the negative binomial model.

{phang}
{opt zip} requests that a likelihood-ratio test comparing the zero-inflated
negative binomial model with the zero-inflated Poisson model be included in
the output.

{marker maximize_options}{...}
{dlgtab:Max options}

{phang}
{it:maximize_options}: {opt dif:ficult}, {opt tech:nique(algorithm_spec)}, 
{opt iter:ate(#)}, [{cmd:{ul:no}}]{cmd:{ul:lo}}{cmd:g}, {opt tr:ace}, 
{opt grad:ient},
{opt showstep},
{opt hess:ian},
{opt shownr:tolerance},
{opt tol:erance(#)}, 
{opt ltol:erance(#)}, {opt gtol:erance(#)}, {opt nrtol:erance(#)}, 
{opt nonrtol:erance}, {opt from(init_specs)}; see {help maximize}.  These
options are seldom used.


{title:Example}

{phang}{cmd:. zinb accidents DayIsMon, inflate(weekend summer) exposure(time)}


{title:Also see}

{psee}
Manual:  {bf:[R] zip}{p_end}

{psee}
Online:  {help zinb postestimation}; {break}  
{helpb constraint},
{helpb glm}, {helpb nbreg},
{helpb poisson}, {helpb xtnbreg},
{helpb zip}, {helpb ztnb}
{p_end}