{smcl}
{* 22APR2010}{...}
{right: also see: {help mvdcmp}}
{hi:help mvdcmpgroup}
{hline}
{title:Title}
{pstd}{hi:mvdcmpgroup} {hline 2} covariate grouping after multivariate decomposition for nonlinear response models
{title:Syntax}
{p 8 16 2}
{cmd:mvdcmpgroup} ({it:aggregate_var} {cmd: :} {it:varlist}) [({it:aggregate_var} {cmd: :} {it:varlist})], {it:options}
{p_end}
{p 4 4 2} where
{p 8 8 2} {it:aggregate_var} specifies the name of a coarser decomposion quantity comprised by
aggregating the individual contributions of the variables appearing in in {it:varlist}.
{synoptset 25 tabbed}{...}
{marker opt}{synopthdr:options}
{synoptline}
{synopt :{opt nocons}}omit constant term from aggregate decomposition
{p_end}
{title:Description}
{pstd} {cmd:mvdcmpgroup} is a companion routine to {cmd:mvdcmp}. It is used as a postestimation
command to generate a coarser decomposition based on grouping several covariates, such as a
collection of socioeconomic variables, that may be informative when considered together as a single
component. This is similar to what is provided by Jann's {it:fairlie}
module.
{title:Examples}
{p 0 15 2} {bf:grouping after decomposition} {p_end}
{pstd} mvdcmpgroup (SES: medu inc1000)
{title:References}
{phang} Jann, B. (2006). fairlie: Stata module to generate nonlinear decomposition of binary outcome
differentials. Available from: {browse "http://ideas.repec.org/c/boc/bocode/s456727.html"}.{p_end}
{title:Authors}
{p 4 4 2}
Daniel A. Powers, University
of Texas at Austin, dpowers@austin.utexas.edu
{p_end}
{p 4 4 2}
Hirotoshi Yoshioka, University of Texas at Austin,
hiro12@prc.utexas.edu
{p_end}
{p 4 4 2}
Myeong-Su Yun, Tulane University, msyun@tulane.edu
{p_end}
{title:Also see}
{p 4 13 2} Online: help for {helpb mvdcmp}, {helpb oaxaca}, and {helpb fairlie}
{p_end}