mlogit.hlp

是一个经济学管理应用软件 很难找的 但是经济学学生又必须用到

{smcl}
{* 11mar2005}{...}
{cmd:help mlogit}{right:dialog:  {bf:{dialog mlogit}}{space 15}}
{right:also see:  {help mlogit postestimation}}
{hline}

{title:Title}

{p2colset 5 19 21 2}{...}
{p2col :{hi:[R] mlogit} {hline 2}}Multinomial (polytomous) logistic
regression{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 15 2}
{cmdab:mlog:it}
{depvar}
[{indepvars}]
{ifin}
{weight}
[{cmd:,} {it:options}]

{synoptset 22 tabbed}{...}
{synopthdr}
{synoptline}
{syntab :Main}
{synopt :{opt noc:onstant}}suppress constant term{p_end}
{synopt :{opt b:aseoutcome(#)}}value of {depvar} that will be the base outcome{p_end}
{synopt :{cmdab:c:onstraints(}{it:{help mlogit##clist:clist}}{cmd:)}}apply specified linear constraints{p_end}

{syntab :SE/Robust}
{synopt :{opth vce(vcetype)}}{it:vcetype} may be {opt r:obust},
{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 rr:r}}report relative-risk ratios{p_end}

{syntab :Max options}
{synopt :{it:{help mlogit##maximize_options:maximize_options}}}control the
maximization process; seldom used{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}{marker clist}
where {it:clist} has the form
{it:#}[{cmd:-}{it:#}][{cmd:,}{it:#}[{cmd:-}{it:#}] {it:...} ]{p_end}

{p 4 6 2}
{opt bootstrap}, {opt by}, {opt jackknife}, {opt rolling}, {opt statsby},
{opt svy}, and {opt xi} are allowed; see {help prefix}.{p_end}
{p 4 6 2}
{opt fweight}s, {opt iweight}s, and {opt pweight}s are allowed;
see {help weight}.{p_end}
{p 4 6 2}
See {help mlogit postestimation} for features available after estimation.{p_end}


{title:Description}

{pstd}
{opt mlogit} fits maximum-likelihood multinomial logit models, also
known as polytomous logistic regression.  You can define constraints to
perform constrained estimation.  Some people refer to conditional logistic
regression as multinomial logit.  If you are one of them, see
{helpb clogit}.

{pstd}
See {help logistic estimation commands} for a list of related estimation
commands.

{pstd}
The model can have a maximum of 50 outcomes with Stata/SE or Intercooled Stata
and 20 outcomes with Small Stata.


{title:Options}

{dlgtab:Model}

{phang}
{opt noconstant}; see {help estimation options}.

{phang}
{opt baseoutcome(#)} specifies the value of {depvar}
to be treated as the base outcome.  The default is to choose the most
frequent outcome.

{phang}
{cmd:constraints(}{it:{help mlogit##clist:clist}}{cmd:)}; see {help estimation options}.

{dlgtab:SE/Robust}

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

{phang}
{opt robust}, {opth cluster(varname)}; see
{help estimation options}. {opt cluster()} can be used with {opt pweight}s
to produce estimates for unstratified cluster-sampled data, but see
{helpb "svy: mlogit"} for a command especially design for survey data.

{dlgtab:Reporting}

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

{phang}
{opt rrr} reports the estimated coefficients transformed to relative
risk ratios, i.e., exp(b) rather than b.  Standard errors and confidence
intervals are similarly transformed.  This option affects how results are
displayed, not how they are estimated.  {opt rrr} may be specified at
estimation or when replaying previously estimated results.

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

{phang}
{it:maximize_options}:
{opt iter:ate(#)},
[{cmdab:no:}]{opt lo:g},
{opt tr:ace},
{opt tol:erance(#)},
{opt ltol:erance(#)};
see {help maximize}.  These options are seldom used.


{title:Examples}

{pstd}
Assume that {opt insure} takes on the values 1, 2, and 3:

{phang2}{cmd:. mlogit insure age male nonwhite site2 site3}{p_end}
{phang2}{cmd:. mlogit, rrr}{p_end}
{phang2}{cmd:. test site2 site3}{p_end}
{phang2}{cmd:. test [1]}{p_end}
{phang2}{cmd:. test [2]:  site2 site3}{p_end}
{phang2}{cmd:. test [1=2]}{p_end}
{phang2}{cmd:. test [1=2]: site2 site3}{p_end}

{pstd}
If {opt insure} is also labeled:

{phang2}{cmd:. label define mylab 1 "Prepaid" 2 "Indem" 3 "Uninsure"}{p_end}
{phang2}{cmd:. mlogit insure age male nonwhite site2 site3}{p_end}
{phang2}{cmd:. test [Prepaid]}{p_end}
{phang2}{cmd:. test [Indem]: site2 site3}{p_end}
{phang2}{cmd:. test [Prepaid=Indem]}{p_end}

{pstd}
Constrained estimation:

{phang2}{cmd:. constraint define 1 [Uninsure]}{p_end}
{phang2}{cmd:. constraint define 2 [Prepaid]: site2 site3}{p_end}
{phang2}{cmd:. mlogit insure age male nonwhite site site3, constr(1) baseout(2)}{p_end}
{phang2}{cmd:. mlogit insure age male nonwhite site site3, constr(2) baseout(2)}{p_end}
{phang2}{cmd:. mlogit insure age male nonwhite site site3, constr(1-2)}


{title:Also see}

{psee}
Manual:  {bf:[R] mlogit}

{psee}
Online:  {help mlogit postestimation};{break}
{helpb constraint},
{helpb clogit},
{helpb logistic},
{helpb logit},
{helpb nlogit},
{helpb ologit},
{helpb slogit},
{helpb "svy: mlogit"}
{p_end}