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1068 lines
41 KiB
Plaintext
1068 lines
41 KiB
Plaintext
9 months ago
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*! version 1.7.6 jsl 2009-10-18
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* - stata 11 minor revisions
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capture program drop mlogtest
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program define mlogtest, rclass
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version 9
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tempname numrhs sample numcats omit chisq df pval
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tempname matiia matsuiia matlr matwald matcomb matlrc nxtrow testn newbase
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tempvar tmp count
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local n = e(N)
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local n "(N=`n')"
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local vers7 "yes"
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local smcl "in smcl "
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local dash "{c -}"
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local vline "{c |}"
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local plussgn "{c +}"
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local topt "{c TT}"
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local bottomt "{c BT}"
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* version 6
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* 13Feb2005
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syntax [varlist(default=none)][, Detail Iia ///
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Hausman Lr Wald Combine LRComb SMhsiao ///
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SUest Set(string) All Base]
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if "`e(cmd)'" != "mlogit" {
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di _newline in y "mlogtest" in r " only works after " in y "mlogit."
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exit
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}
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* store estimation results from original mlogit as _X
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qui estimates store _X
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*-> set defaults
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local dolr = "no"
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if "`lr'"!="" {
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local dolr = "yes"
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}
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local doiia = "no"
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if "`hausman'"!="" | "`iia'"!="" {
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local doiia = "yes"
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}
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local doshiia = "no"
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if "`smhsiao'"!="" | "`iia'"!="" {
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local doshiia = "yes"
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}
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local dosuiia = "no"
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if "`suest'"!="" | "`iia'"!="" {
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local dosuiia = "yes"
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}
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local dowald = "no"
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if "`wald'"!="" {
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local dowald = "yes"
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}
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local docomb = "no"
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if "`combine'"!="" {
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local docomb = "yes"
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}
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local dolrcom = "no"
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if "`lrcomb'"!="" {
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local dolrcom = "yes"
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}
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if "`all'"!="" {
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local dolr = "yes"
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local doiia = "yes"
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local doshiia = "yes"
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* local dosuiia = "yes"
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local dowald = "yes"
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local docomb = "yes"
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local dolrcom = "yes"
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}
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*-> get weight info from last mlogit
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local wtis ""
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if "`e(wtype)'"!="" {
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local wtis "[`e(wtype)'`e(wexp)']"
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}
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*-> check that estimation sample matches n from regression
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qui gen `sample' = e(sample)
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if "`e(wtype)'"=="" | "`e(wtype)'"=="aweight" | "`e(wtype)'"=="pweight" {
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qui count if `sample' == 1
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scalar `testn' = r(N)
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}
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if "`e(wtype)'"=="fweight" | "`e(wtype)'"=="iweight" {
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local wtexp = substr("`e(wexp)'", 3, .)
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gen `tmp' = (`wtexp')*`sample'
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qui su `tmp', meanonly
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scalar `testn' = round(r(sum),1)
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}
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if e(N) ~= `testn' {
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di _newline in r "Data has been altered since " /*
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*/ in y "mlogit" in r " was estimated."
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exit
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}
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*-> get information about the mlogit
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local depvar = "`e(depvar)'"
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local printdv = abbrev("`printdv'", 8)
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_perhs
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local rhsnam "`r(rhsnms)'"
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scalar `numrhs' = `r(nrhs)'
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_pecats
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local catnms8 "`r(catnms8)'"
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local catvals "`r(catvals)'"
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local catnms "`r(catnms)'"
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scalar `numcats' = r(numcats)
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* 2007-06-29 stata 10
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if c(stata_version) < 10 {
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local basecat = e(basecat) /* or r(refval) */
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}
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else {
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local basecat = e(baseout) /* or r(refval) */
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}
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local refnm "`r(refnm)'"
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local check : word count `catvals'
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if `numcats' ~= real("`check'") {
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di _newline in r "Problem determining number of categories."
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}
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*-> parse out sets if set option on
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local numset = 0
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if "`set'" ~= "" {
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tokenize "`set'", parse("\")
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local count = 1
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while "``count''"!="" {
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if "``count''"=="\" {
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macro shift
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}
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else {
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local set`count' "``count''"
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capture unab set`count': /*
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*/ `set`count'', min(2) name(defining sets)
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local setl`count': word count `set`count''
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* check if all variables in set are rhs variables
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local count2 = 1
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while `count2' <= `setl`count'' {
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local count3 = 1
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local inrhs "no"
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local setvar : word `count2' of `set`count''
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while `count3' <= `numrhs' {
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local ivar : word `count3' of `rhsnam'
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if "`setvar'"=="`ivar'" {
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local inrhs "yes"
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}
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local count3 = `count3' + 1
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}
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if "`inrhs'" == "no" {
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di _newline in r "variable " in y "`setvar'" in r /*
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*/ " specified in set() but is not in model."
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exit
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}
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local count2 = `count2' + 1
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} /* while count2 <= `setl`count' */
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return local set_`count' "`set`count''"
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local count = `count' + 1
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} /* else */
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} /* while "``count''"!="" */
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local numset = `count' - 1
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} /* if "`set'" ~= "" */
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*-> LR test of independent variables
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version 7
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if "`dolr'"=="yes" & `numrhs' == 0 {
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di _n in r "LR test cannot be computed on intercept-only model."
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}
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else if "`dolr'"=="yes" {
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di _newline in g /*
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*/ "**** Likelihood-ratio tests for independent variables `n'"
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di _newline in g /*
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*/ " Ho: All coefficients associated with given variable(s) are 0."
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di `smcl' _newline in g %12s "`printdv'" _col(14) "`vline'" /*
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*/ _col(22) "chi2" _col(29) "df" _col(34) "P>chi2"
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di `smcl' in g _dup(13) "`dash'" "`plussgn'" _dup(25) "`dash'"
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lrtest, saving(0)
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* 13Feb2005 - allow tests of specified # of variables
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if "`varlist'"!="" { // if var list
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local nvlist : word count `varlist'
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local ntests = `nvlist' // use this as the # of rhsvars
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local testnms "`varlist'"
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}
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else {
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local testnms "`rhsnam'"
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local ntests = `numrhs'
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}
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tokenize "`rhsnam'" // tokenize list, rather than rhs vars
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* 13Feb2005 replace numrhs with ntests below
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* loop over all rhs + specified sets
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local count = 1
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while `count' <= `ntests'+`numset' {
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local testvar : word `count' of `testnms'
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* for individual independent variables
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if `count' <= `ntests' {
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local var`count' : word `count' of `testnms'
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* create varlist with all vars but count variable
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local count2 = 1
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local lrrhs = ""
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while `count2' <= `numrhs' { // loop through all variables
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if "`testvar'"!="``count2''" {
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local lrrhs "`lrrhs' ``count2''"
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}
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local count2 = `count2' + 1
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}
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} /* if `count' <= `ntests' */
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* for sets of independent variables
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if `count' > `ntests' {
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local thisset = `count'-`ntests'
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* for matrix & output rowname
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local var`count' "set_`thisset'"
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* for count3 loop
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local countto : word count `set`thisset''
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local count2 = 1
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local lrrhs = ""
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while `count2' <= `ntests' {
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local count3 = 1
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local inset "no"
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while `count3' <= `countto' {
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local setvar : word `count3' of `set`thisset''
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if "``count2''"=="`setvar'" {
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local inset "yes"
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}
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local count3 = `count3' + 1
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}
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if "`inset'" == "no" {
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local lrrhs "`lrrhs' ``count2''"
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}
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local count2 = `count2' + 1
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}
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} /* if `count' > `ntests' */
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qui mlogit `depvar' `lrrhs' `wtis' /*
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*/ if `sample' == 1, b(`basecat')
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* quietly lrtest, using(0)
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qui lrtest, using(0)
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* put results in matrix
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scalar `chisq' = r(chi2)
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scalar `df' = r(df)
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scalar `pval' = r(p)
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if `pval' == . {
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scalar `pval' = -9999
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}
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mat `nxtrow' = `chisq', `df', `pval'
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mat rownames `nxtrow' = "`var`count''"
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mat `matlr' = nullmat(`matlr') \ `nxtrow'
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local count = `count' + 1
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} /* while `count' <= `ntests' */
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mat colnames `matlr' = chi2 df p
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* cycle through row by row of output matrix and print
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local countto = rowsof(`matlr')
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local count = 1
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while `count' <= `countto' {
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scalar `chisq' = `matlr'[`count', 1]
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scalar `df' = `matlr'[`count', 2]
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scalar `pval' = `matlr'[`count', 3]
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if `pval' == -9999 {
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scalar `pval' = .
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}
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* tests of individual variables
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if `count' <= `ntests' {
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* name to print
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local printnm "`var`count''"
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local printnm = abbrev("`printnm'", 12)
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di `smcl' in y %12s "`printnm'" _col(14) in g "`vline'" /*
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*/ _col(17) %9.3f in y `chisq' /*
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*/ _col(26) %5.0f `df' /*
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*/ _col(35) %4.3f `pval'
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}
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* tests of sets
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if `count' > `ntests' {
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local thisset = `count' - `ntests'
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di `smcl' in g _dup(13) "`dash'" "`plussgn'" _dup(25) "`dash'"
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* name to print
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local printnm "`var`count''"
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local printnm = abbrev("`printnm'", 12)
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di `smcl' in g %12s "`printnm':" _col(14) in g "`vline'" /*
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*/ _col(17) %9.3f in y `chisq' /*
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*/ _col(26) %5.0f `df' /*
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*/ _col(35) %4.3f `pval'
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local count2 = 1
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local countt2 : word count `set`thisset''
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while `count2' <= `countt2' {
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local setvar : word `count2' of `set`thisset''
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* name to print
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local printnm "`setvar'"
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if "`vers7'"=="yes" { local printnm = abbrev("`printnm'", 12) }
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di `smcl' %12s in y "`printnm'" _col(14) in g "`vline'"
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local count2 = `count2' + 1
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}
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}
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local count = `count' + 1
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} /* while `count' <= `countto' */
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di `smcl' in g _dup(13) "`dash'" "`bottomt'" _dup(25) "`dash'"
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qui version 9: estimates restore _X
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return matrix lrtest `matlr'
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} /* if "`dolr'"=="yes" */
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||
|
|
|
||
|
|
*-> WALD test of independent variables
|
||
|
|
|
||
|
|
version 7
|
||
|
|
* 13Feb2005 - allow tests of specified # of variables
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||
|
|
if "`varlist'"!="" { // if var list
|
||
|
|
local nvlist : word count `varlist'
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|
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local testnms "`varlist'"
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|
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local ntests = `nvlist' // use this as the # of rhsvars
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|
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}
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|
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else {
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|
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local ntests = `numrhs'
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local testnms "`rhsnam'"
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}
|
||
|
|
|
||
|
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if "`dowald'"=="yes" & `ntests' == 0 {
|
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|
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di _n in r "Wald test cannot be computed on intercept-only model."
|
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|
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}
|
||
|
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else if "`dowald'"=="yes" {
|
||
|
|
* 13Feb2005 replace numrhs with ntests below
|
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|
|
tokenize "`testnms'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** Wald tests for independent variables `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: All coefficients associated with given variable(s) are 0."
|
||
|
|
di `smcl' _newline in g %12s "`printdv'" _col(14) "`vline'" /*
|
||
|
|
*/ _col(22) "chi2" _col(29) "df" _col(34) "P>chi2"
|
||
|
|
di `smcl' in g _dup(13) "`dash'" "`plussgn'" _dup(25) "`dash'"
|
||
|
|
|
||
|
|
* loop over all rhs + specified sets
|
||
|
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local count = 1
|
||
|
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while `count' <= `ntests'+`numset' {
|
||
|
|
* for individual independent variables
|
||
|
|
if `count' <= `ntests' {
|
||
|
|
* 13Feb2005
|
||
|
|
local var`count' : word `count' of `testnms'
|
||
|
|
qui test `var`count''
|
||
|
|
}
|
||
|
|
* tests of sets
|
||
|
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if `count' > `ntests' {
|
||
|
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local thisset = `count'-`ntests'
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|
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*get set name/number for matrix&output
|
||
|
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local var`count' "set_`thisset'"
|
||
|
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qui test `set`thisset''
|
||
|
|
}
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
if `pval' == . { scalar `pval' = -9999 }
|
||
|
|
mat `nxtrow' = `chisq', `df', `pval'
|
||
|
|
mat rownames `nxtrow' = "`var`count''"
|
||
|
|
mat `matwald' = nullmat(`matwald') \ `nxtrow'
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while `count' <= `ntests' */
|
||
|
|
|
||
|
|
mat colnames `matwald' = chi2 df p
|
||
|
|
local countto = rowsof(`matwald')
|
||
|
|
local count = 1
|
||
|
|
while `count' <= `countto' {
|
||
|
|
scalar `chisq' = `matwald'[`count', 1]
|
||
|
|
scalar `df' = `matwald'[`count', 2]
|
||
|
|
scalar `pval' = `matwald'[`count', 3]
|
||
|
|
if `pval' == -9999 { scalar `pval' = . }
|
||
|
|
if `count' <= `ntests' {
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`var`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 12)
|
||
|
|
di `smcl' in y %12s "`printnm'" _col(14) in g "`vline'" /*
|
||
|
|
*/ _col(17) %9.3f in y `chisq' /*
|
||
|
|
*/ _col(26) %5.0f `df' /*
|
||
|
|
*/ _col(35) %4.3f `pval'
|
||
|
|
}
|
||
|
|
if `count' > `ntests' {
|
||
|
|
local thisset = `count' - `ntests'
|
||
|
|
di `smcl' in g _dup(13) "`dash'" "`plussgn'" _dup(25) "`dash'"
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`var`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 12)
|
||
|
|
di `smcl' in g %12s "`printnm':" _col(14) in g "`vline'" /*
|
||
|
|
*/ _col(17) %9.3f in y `chisq' /*
|
||
|
|
*/ _col(26) %5.0f `df' /*
|
||
|
|
*/ _col(35) %4.3f `pval'
|
||
|
|
local count2 = 1
|
||
|
|
local countt2 : word count `set`thisset''
|
||
|
|
while `count2' <= `countt2' {
|
||
|
|
local setvar : word `count2' of `set`thisset''
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`setvar'"
|
||
|
|
if "`vers7'"=="yes" {
|
||
|
|
local printnm = abbrev("`printnm'", 12)
|
||
|
|
}
|
||
|
|
di `smcl' %12s in y "`printnm'" _col(14) in g "`vline'"
|
||
|
|
local count2 = `count2' + 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while `count' <= `countto' */
|
||
|
|
di `smcl' in g _dup(13) "`dash'" "`bottomt'" _dup(25) "`dash'"
|
||
|
|
return matrix wald `matwald'
|
||
|
|
} /* if "`dowald'"=="yes" */
|
||
|
|
|
||
|
|
*-> HAUSMAN IIA Test
|
||
|
|
|
||
|
|
version 9
|
||
|
|
* can't do if only two categories
|
||
|
|
if "`doiia'"=="yes" & `numcats' == 2 {
|
||
|
|
di _n in r /*
|
||
|
|
*/ "Hausman IIA test requires at least 3 dependent categories."
|
||
|
|
}
|
||
|
|
else if "`doiia'"=="yes" {
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** Hausman tests of IIA assumption `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: Odds(Outcome-J vs Outcome-K) are independent of "/*
|
||
|
|
*/ "other alternatives."
|
||
|
|
|
||
|
|
* cycle through all alternatives
|
||
|
|
tokenize "`catvals'"
|
||
|
|
local count = 1
|
||
|
|
while real("`count'") <= `numcats' {
|
||
|
|
local lab`count' : word `count' of `catnms'
|
||
|
|
local slab`count' : word `count' of `catnms8'
|
||
|
|
scalar `omit' = real("``count''")
|
||
|
|
if "`detail'" == "detail" {
|
||
|
|
if "`lab`count''"!="``count''" {
|
||
|
|
di _newline in g/*
|
||
|
|
*/ "Hausman test when omitted alternative is " in y `omit' /*
|
||
|
|
*/ in g " (" in y "`lab`count''" in g ")"
|
||
|
|
/* di _newline in g/*
|
||
|
|
*/ "Hausman test when omitted outcome is " in y `omit' /*
|
||
|
|
*/ in g " (" in y "`lab`count''" in g ")"
|
||
|
|
*/
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
di in g _newline /*
|
||
|
|
*/ "Hausman test when omitted alternative is " in y `omit'
|
||
|
|
}
|
||
|
|
} /* if "`detail'" == "detail" */
|
||
|
|
if `omit'==real("`basecat'") & "`base'" != "" {
|
||
|
|
* IIA for basecategory requires estimating mlogit with
|
||
|
|
* new basecategory. Make new basecat the largest category
|
||
|
|
* of the dependent variable that is not the original basecat
|
||
|
|
local maxcnt = 0
|
||
|
|
local count2 = 1
|
||
|
|
while `count2' <= `numcats' {
|
||
|
|
if real("``count2''") != `omit' {
|
||
|
|
qui count if `depvar'==``count2'' & `sample'==1
|
||
|
|
if r(N)>`maxcnt' {
|
||
|
|
local newbase = ``count2''
|
||
|
|
local maxcnt = r(N)
|
||
|
|
local tmplab : word `count2' of `catnms'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local count2 = `count2' + 1
|
||
|
|
} /* while count2 <= `numcats' */
|
||
|
|
|
||
|
|
* estimates of old logit are held in _X
|
||
|
|
qui mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample' == 1, b(`newbase')
|
||
|
|
qui estimates store _Xnb
|
||
|
|
|
||
|
|
qui mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample'==1 & `depvar'!=`omit', b(`newbase')
|
||
|
|
if "`detail'"=="detail" {
|
||
|
|
if "`lab`count''"!="``count''" {
|
||
|
|
di in g "(Using category " in g "`newbase' " /*
|
||
|
|
*/ in g "(" in g "`tmplab'" in g /*
|
||
|
|
*/ ") as comparison group)"
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
di in g "(Using category " in g "`newbase' " /*
|
||
|
|
*/ in g "as comparison group)"
|
||
|
|
}
|
||
|
|
hausman . _Xnb, alleq constant
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui hausman . _Xnb, alleq constant
|
||
|
|
}
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
if `pval' == . | `chisq' < 0 {
|
||
|
|
scalar `pval' = -9999
|
||
|
|
}
|
||
|
|
|
||
|
|
*put things back and then hold them again
|
||
|
|
qui estimates restore _X
|
||
|
|
mat `nxtrow' = `omit', `chisq', `df', `pval'
|
||
|
|
mat rownames `nxtrow' = "`slab`count''"
|
||
|
|
mat `matiia' = nullmat(`matiia') \ `nxtrow'
|
||
|
|
} /* if `omit'==real("`basecat'") */
|
||
|
|
else if `omit'!=real("`basecat'") {
|
||
|
|
quietly mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample' == 1 & `depvar' != `omit', b(`basecat')
|
||
|
|
if "`detail'"=="detail" {
|
||
|
|
hausman . _X, alleq constant
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui hausman . _X, alleq constant
|
||
|
|
}
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
if `pval' == . | `chisq' < 0 {
|
||
|
|
scalar `pval' = -9999
|
||
|
|
}
|
||
|
|
mat `nxtrow' = `omit', `chisq', `df', `pval'
|
||
|
|
mat rownames `nxtrow' = "`slab`count''"
|
||
|
|
mat `matiia' = nullmat(`matiia') \ `nxtrow'
|
||
|
|
} /* else if `omit'!=real("`basecat'") */
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while real("`count'") <= `numcats' */
|
||
|
|
|
||
|
|
mat colnames `matiia' = omitted chi2 df p
|
||
|
|
if "`detail'" == "detail" {
|
||
|
|
di in g _newline "*** Summary of results"
|
||
|
|
}
|
||
|
|
|
||
|
|
* only print explainer if negative chi2 observed
|
||
|
|
local anyneg = "no"
|
||
|
|
local countto = rowsof(`matiia')
|
||
|
|
local count = 1
|
||
|
|
|
||
|
|
di _newline `smcl' in g " Omitted" _col(10) "`vline'" /*
|
||
|
|
*/ _col(17) "chi2" _col(24) "df" _col(29) "P>chi2" _col(38) "evidence"
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`plussgn'" _dup(36) "`dash'"
|
||
|
|
|
||
|
|
*cycle through row by row of output matrix and print
|
||
|
|
while `count' <= `countto' {
|
||
|
|
scalar `chisq' = `matiia'[`count', 2]
|
||
|
|
scalar `df' = `matiia'[`count', 3]
|
||
|
|
scalar `pval' = `matiia'[`count', 4]
|
||
|
|
if `pval' == -9999 {
|
||
|
|
local anyneg "yes"
|
||
|
|
local implies "---"
|
||
|
|
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`slab`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 8)
|
||
|
|
|
||
|
|
di `smcl' in y %8s "`printnm'" _col(10) in g "`vline'" /*
|
||
|
|
*/ _col(13) %8.3f in y `chisq' /*
|
||
|
|
*/ _col(21) %5.0f `df' /*
|
||
|
|
*/ _col(30) " ---" /*
|
||
|
|
*/ _col(38) %-10s "`implies'"
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local implies "for Ho"
|
||
|
|
if `pval' < .05 {
|
||
|
|
local implies "against Ho"
|
||
|
|
}
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`slab`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 12)
|
||
|
|
|
||
|
|
di `smcl' %8s in y "`printnm'" _col(10) in g "`vline'" /*
|
||
|
|
*/ _col(13) %8.3f in y `chisq' /*
|
||
|
|
*/ _col(21) %5.0f `df' /*
|
||
|
|
*/ _col(30) %4.3f `pval' /*
|
||
|
|
*/ _col(38) %-10s "`implies'"
|
||
|
|
}
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while `count' <= `countto' */
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`bottomt'" _dup(36) "`dash'"
|
||
|
|
|
||
|
|
if "`anyneg'" == "yes" {
|
||
|
|
di in g " Note: If chi2<0, the estimated model does not"
|
||
|
|
di in g " meet asymptotic assumptions of the test."
|
||
|
|
}
|
||
|
|
|
||
|
|
qui estimates restore _X
|
||
|
|
return matrix hausman `matiia'
|
||
|
|
|
||
|
|
} /* if "`doiia'"=="no" */
|
||
|
|
|
||
|
|
*-> suest-based HAUSMAN IIA Test
|
||
|
|
|
||
|
|
version 9
|
||
|
|
* see if cluster has been used and, if so, this can be incorporated in suest
|
||
|
|
local clustvar = e(clustvar)
|
||
|
|
* can't do if only two categories
|
||
|
|
if "`dosuiia'"=="yes" & `numcats' == 2 {
|
||
|
|
di _n in r ///
|
||
|
|
"suest-based Hausman IIA test requires at least 3 dependent categories."
|
||
|
|
}
|
||
|
|
else if ("`clustvar'" != "." & "`clustvar'" != "") {
|
||
|
|
di _n as err ///
|
||
|
|
"suest-based Hausman IIA test must be estimated differently when cluster()"
|
||
|
|
di as err "is specified, see [R] suest"
|
||
|
|
}
|
||
|
|
else if "`dosuiia'"=="yes" {
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** suest-based Hausman tests of IIA assumption `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: Odds(Outcome-J vs Outcome-K) are independent of "/*
|
||
|
|
*/ "other alternatives."
|
||
|
|
|
||
|
|
* cycle through all alternatives
|
||
|
|
tokenize "`catvals'"
|
||
|
|
local count = 1
|
||
|
|
while real("`count'") <= `numcats' {
|
||
|
|
local lab`count' : word `count' of `catnms'
|
||
|
|
local slab`count' : word `count' of `catnms8'
|
||
|
|
scalar `omit' = real("``count''")
|
||
|
|
if `omit'==real("`basecat'") & "`base'" != "" {
|
||
|
|
* IIA for basecategory requires estimating mlogit with
|
||
|
|
* new basecategory. Make new basecat the largest category
|
||
|
|
* of the dependent variable that is not the original basecat
|
||
|
|
local maxcnt = 0
|
||
|
|
local count2 = 1
|
||
|
|
while `count2' <= `numcats' {
|
||
|
|
if real("``count2''") != `omit' {
|
||
|
|
qui count if `depvar'==``count2'' & `sample'==1
|
||
|
|
if r(N)>`maxcnt' {
|
||
|
|
local newbase = ``count2''
|
||
|
|
local maxcnt = r(N)
|
||
|
|
local tmplab : word `count2' of `catnms'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local count2 = `count2' + 1
|
||
|
|
} /* while count2 <= `numcats' */
|
||
|
|
|
||
|
|
* estimates of old logit are held in _X
|
||
|
|
qui mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample' == 1, b(`newbase')
|
||
|
|
qui estimates store _Xnb
|
||
|
|
|
||
|
|
qui mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample'==1 & `depvar'!=`omit', b(`newbase')
|
||
|
|
qui estimates store _Y
|
||
|
|
local eqnames = e(eqnames)
|
||
|
|
qui estimates store _Y
|
||
|
|
qui suest _Y _Xnb
|
||
|
|
qui estimates store _suest
|
||
|
|
|
||
|
|
foreach name in `eqnames' {
|
||
|
|
* di `"`eqnames'"'
|
||
|
|
qui test [_Xnb_`name' = _Y_`name'], cons accum
|
||
|
|
}
|
||
|
|
if "`detail'"=="detail" {
|
||
|
|
suest
|
||
|
|
test
|
||
|
|
}
|
||
|
|
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
if `pval' == . | `chisq' < 0 {
|
||
|
|
scalar `pval' = -9999
|
||
|
|
}
|
||
|
|
|
||
|
|
*put things back and then hold them again
|
||
|
|
qui estimates restore _X
|
||
|
|
mat `nxtrow' = `omit', `chisq', `df', `pval'
|
||
|
|
mat rownames `nxtrow' = "`slab`count''"
|
||
|
|
mat `matsuiia' = nullmat(`matsuiia') \ `nxtrow'
|
||
|
|
|
||
|
|
} /* if `omit'==real("`basecat'") */
|
||
|
|
else if `omit'!=real("`basecat'") {
|
||
|
|
quietly mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample' == 1 & `depvar' != `omit', b(`basecat')
|
||
|
|
local eqnames = e(eqnames)
|
||
|
|
qui estimates store _Y
|
||
|
|
qui suest _Y _X
|
||
|
|
qui estimates store _suest
|
||
|
|
|
||
|
|
** execute tests
|
||
|
|
foreach name in `eqnames' {
|
||
|
|
* di `"`eqnames'"'
|
||
|
|
qui test [_X_`name' = _Y_`name'], cons accum
|
||
|
|
}
|
||
|
|
if "`detail'"=="detail" {
|
||
|
|
suest
|
||
|
|
test
|
||
|
|
}
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
if `pval' == . | `chisq' < 0 {
|
||
|
|
scalar `pval' = -9999
|
||
|
|
}
|
||
|
|
qui estimates restore _X
|
||
|
|
mat `nxtrow' = `omit', `chisq', `df', `pval'
|
||
|
|
mat rownames `nxtrow' = "`slab`count''"
|
||
|
|
mat `matsuiia' = nullmat(`matsuiia') \ `nxtrow'
|
||
|
|
} /* else if `omit'!=real("`basecat'") */
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while real("`count'") <= `numcats' */
|
||
|
|
|
||
|
|
mat colnames `matsuiia' = omitted chi2 df p
|
||
|
|
local anyneg = "no"
|
||
|
|
local countto = rowsof(`matsuiia')
|
||
|
|
local count = 1
|
||
|
|
|
||
|
|
di _newline `smcl' in g " Omitted" _col(10) "`vline'" /*
|
||
|
|
*/ _col(17) "chi2" _col(24) "df" _col(29) "P>chi2" _col(38) "evidence"
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`plussgn'" _dup(36) "`dash'"
|
||
|
|
|
||
|
|
*cycle through row by row of output matrix and print
|
||
|
|
while `count' <= `countto' {
|
||
|
|
scalar `chisq' = `matsuiia'[`count', 2]
|
||
|
|
scalar `df' = `matsuiia'[`count', 3]
|
||
|
|
scalar `pval' = `matsuiia'[`count', 4]
|
||
|
|
if `pval' == -9999 {
|
||
|
|
local anyneg "yes"
|
||
|
|
local implies "---"
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`slab`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 8)
|
||
|
|
|
||
|
|
di `smcl' in y %8s "`printnm'" _col(10) in g "`vline'" /*
|
||
|
|
*/ _col(13) %8.3f in y `chisq' /*
|
||
|
|
*/ _col(21) %5.0f `df' /*
|
||
|
|
*/ _col(30) " ---" /*
|
||
|
|
*/ _col(38) %-10s "`implies'"
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local implies "for Ho"
|
||
|
|
if `pval' < .05 {
|
||
|
|
local implies "against Ho"
|
||
|
|
}
|
||
|
|
*added for stata 7 compatibility
|
||
|
|
local printnm "`slab`count''"
|
||
|
|
local printnm = abbrev("`printnm'", 12)
|
||
|
|
|
||
|
|
di `smcl' %8s in y "`printnm'" _col(10) in g "`vline'" /*
|
||
|
|
*/ _col(13) %8.3f in y `chisq' /*
|
||
|
|
*/ _col(21) %5.0f `df' /*
|
||
|
|
*/ _col(30) %4.3f `pval' /*
|
||
|
|
*/ _col(38) %-10s "`implies'"
|
||
|
|
}
|
||
|
|
local count = `count' + 1
|
||
|
|
} /* while `count' <= `countto' */
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`bottomt'" _dup(36) "`dash'"
|
||
|
|
|
||
|
|
qui estimates restore _X
|
||
|
|
return matrix suest `matsuiia'
|
||
|
|
} /* if "`doiia'"=="no" */
|
||
|
|
|
||
|
|
*-> Small-Hsiao test of iia
|
||
|
|
|
||
|
|
version 7
|
||
|
|
* NOTE: THE CODE FOR COMPUTING THE SMALL-HSIAO TEST IS ADAPTED
|
||
|
|
* FROM CODE WRITTEN BY NICK WINTER (IN HIS -SMHSIAO- COMMAND)
|
||
|
|
|
||
|
|
* 050219 fix error in df for sh test
|
||
|
|
|
||
|
|
*can't do if only two categories
|
||
|
|
if "`doshiia'"=="yes" & `numcats' == 2 {
|
||
|
|
di _n in r "Small-Hsiao IIA test requires at least 3 dependent categories."
|
||
|
|
}
|
||
|
|
else if "`doshiia'"=="yes" {
|
||
|
|
tempname rowres matsh touse
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** Small-Hsiao tests of IIA assumption `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: Odds(Outcome-J vs Outcome-K) are independent of other alternatives."
|
||
|
|
qui gen `touse' = e(sample)
|
||
|
|
|
||
|
|
tempvar samp
|
||
|
|
qui gen `samp'=round(uniform(),1)+1 if `touse'
|
||
|
|
local y `e(depvar)'
|
||
|
|
tempvar tempy
|
||
|
|
qui gen `tempy' = `depvar'
|
||
|
|
local varlist "`tempy' `rhsnam'"
|
||
|
|
*local dof = `numrhs' + 1
|
||
|
|
qui ta `tempy' if `touse' & `samp'==1
|
||
|
|
local cat1 `r(r)'
|
||
|
|
qui ta `tempy' if `touse' & `samp'==2
|
||
|
|
local cat2 `r(r)'
|
||
|
|
if `cat1'!=`numcats' | `cat2'!=`numcats' {
|
||
|
|
di in r /*
|
||
|
|
*/ "Random draw yielded empty cells for some categories of `y' in"
|
||
|
|
di in r /*
|
||
|
|
*/ "one of the half-samples. Could not estimate Small-Hsiao test."
|
||
|
|
error 148
|
||
|
|
}
|
||
|
|
|
||
|
|
local count = 1
|
||
|
|
local countto = `numcats' - 1
|
||
|
|
if "`base'"!="" {
|
||
|
|
local countto = `numcats'
|
||
|
|
}
|
||
|
|
while `count' <= `countto' {
|
||
|
|
local bcat "b(`basecat')"
|
||
|
|
if `count'==`numcats' {
|
||
|
|
local bcat ""
|
||
|
|
}
|
||
|
|
local elim : word `count' of `catvals'
|
||
|
|
local ielim `elim'
|
||
|
|
tempname Vals
|
||
|
|
qui tab `tempy' if `touse', matrow(`Vals')
|
||
|
|
local nEvals = `numcats'-1
|
||
|
|
local Yvals = ""
|
||
|
|
local EYvals = ""
|
||
|
|
local EYeqs = ""
|
||
|
|
local i = 1
|
||
|
|
while `i' <= `numcats' {
|
||
|
|
local Yval`i' = `Vals'[`i',1]
|
||
|
|
local Yvals "`Yvals' `Yval`i''"
|
||
|
|
if `Yval`i'' != `elim' {
|
||
|
|
local EYvals "`EYvals' `Yval`i''"
|
||
|
|
local EYeqs "`EYeqs' `i'"
|
||
|
|
local Ylab`i' `Yval`i''
|
||
|
|
}
|
||
|
|
local i = `i' + 1
|
||
|
|
}
|
||
|
|
|
||
|
|
tempvar lnL denom
|
||
|
|
tempname b0a b0b b0ab b1b
|
||
|
|
|
||
|
|
qui mlogit `varlist' /*
|
||
|
|
*/ if (`touse' & `samp'==2 & `tempy'!=`elim') `wtis', `bcat'
|
||
|
|
*spost9 df for SH 19Feb2005
|
||
|
|
tempname v
|
||
|
|
mat `v' = e(V)
|
||
|
|
local dof = rowsof(`v')
|
||
|
|
local lnL_1 = e(ll)
|
||
|
|
if `count'==`numcats' {
|
||
|
|
local tmpbcat "`e(basecat)'"
|
||
|
|
local bcat "b(`tmpbcat')"
|
||
|
|
}
|
||
|
|
*ESTIMATE MODELS FOR EACH HALF SAMPLE
|
||
|
|
qui mlogit `varlist' if `touse' & `samp'==1 `wtis', `bcat'
|
||
|
|
mat `b0a' = e(b)
|
||
|
|
qui mlogit `varlist' if `touse' & `samp'==2 `wtis', `bcat'
|
||
|
|
mat `b0b' = e(b)
|
||
|
|
* Zhang & Hoffman eq. 9
|
||
|
|
mat `b0ab' = (0.70710678)*(`b0a') + (0.29289322)*(`b0b')
|
||
|
|
|
||
|
|
* get LnL for amalgamated coefficients
|
||
|
|
*get XBs & assemble denominator
|
||
|
|
qui gen double `denom' = 0 if `touse'
|
||
|
|
local i 1
|
||
|
|
* cycle through values (w/o eliminated one)
|
||
|
|
while `i' <= (`numcats'-1) {
|
||
|
|
local cury : word `i' of `EYvals'
|
||
|
|
local cureq : word `i' of `EYeqs'
|
||
|
|
tempvar xb`cureq'
|
||
|
|
if `cury' != `basecat' & "`cury'" != "`tmpbcat'" {
|
||
|
|
matrix score double `xb`cureq'' = `b0ab' /*
|
||
|
|
*/ if `touse', eq(`Ylab`cureq'')
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui gen double `xb`cureq''=0 /* because (exp(0)=1) */
|
||
|
|
}
|
||
|
|
qui replace `denom'=`denom' + exp(`xb`cureq'') if `touse'
|
||
|
|
local i=`i'+1
|
||
|
|
}
|
||
|
|
|
||
|
|
* create Log likelihood using amalgamated coeff.
|
||
|
|
qui gen double `lnL' = . if `touse'
|
||
|
|
local i 1
|
||
|
|
while `i'<=`nEvals' {
|
||
|
|
local cureq : word `i' of `EYeqs'
|
||
|
|
local cury : word `i' of `EYvals'
|
||
|
|
qui replace `lnL' = ln(exp(`xb`cureq'')/(`denom')) /*
|
||
|
|
*/ if `tempy'==`cury' & `touse'
|
||
|
|
local i=`i'+1
|
||
|
|
}
|
||
|
|
|
||
|
|
* GET LnL, only for observations in the 2d sample
|
||
|
|
* and without eliminated observations:
|
||
|
|
sum `lnL' if `touse' & `samp'==2 & `tempy'!=`elim', meanonly
|
||
|
|
local lnL_0 = r(sum)
|
||
|
|
local SH = -2 * (`lnL_0' - `lnL_1')
|
||
|
|
local p = chiprob(`dof',`SH')
|
||
|
|
mat `rowres' = `elim' , `lnL_0' , `lnL_1' , `SH' , `dof' , `p'
|
||
|
|
mat rownames `rowres' = "test `count'"
|
||
|
|
mat colnames `rowres' = elim_cat lnL_0 lnL_1 chi2 df p
|
||
|
|
mat `matsh' = nullmat(`matsh') \ `rowres'
|
||
|
|
local count = `count' + 1
|
||
|
|
}
|
||
|
|
|
||
|
|
di _newline `smcl' in g " Omitted" _col(10) "`vline'" /*
|
||
|
|
*/ _col(13) "lnL(full)" _col(24) "lnL(omit)" /*
|
||
|
|
*/ _col(37) "chi2" _col(44) "df" _col(49) "P>chi2" _col(58) "evidence"
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`plussgn'" _dup(57) "`dash'"
|
||
|
|
local count = 1
|
||
|
|
local countto = rowsof(`matsh')
|
||
|
|
while `count' <= `countto' {
|
||
|
|
local elim = `matsh'[`count', 1]
|
||
|
|
local elimnm8 : word `count' of `catnms8'
|
||
|
|
local lnL_0 = `matsh'[`count', 2]
|
||
|
|
local lnL_1 = `matsh'[`count', 3]
|
||
|
|
local SH = `matsh'[`count', 4]
|
||
|
|
scalar `df' = `matsh'[`count', 5]
|
||
|
|
scalar `pval' = `matsh'[`count', 6]
|
||
|
|
local count = `count' + 1
|
||
|
|
local implies "for Ho"
|
||
|
|
if `pval' < .05 {
|
||
|
|
local implies "against Ho"
|
||
|
|
}
|
||
|
|
di `smcl' in y %8s "`elimnm8'" _col(10) in g "`vline'" /*
|
||
|
|
*/ _col(13) %9.3f in y `lnL_0' /*
|
||
|
|
*/ _col(24) %9.3f `lnL_1' /*
|
||
|
|
*/ _col(33) %8.3f `SH' /*
|
||
|
|
*/ _col(41) %5.0f `df' /*
|
||
|
|
*/ _col(50) %4.3f `pval' /*
|
||
|
|
*/ _col(58) %-10s "`implies'"
|
||
|
|
}
|
||
|
|
di `smcl' in g _dup(9) "`dash'" "`bottomt'" _dup(57) "`dash'"
|
||
|
|
|
||
|
|
qui mat list `matsh'
|
||
|
|
qui version 9: estimates restore _X
|
||
|
|
return matrix smhsiao `matsh'
|
||
|
|
} /* if "`doshiia'"=="no" */
|
||
|
|
|
||
|
|
*-> Wald tests for combining categories
|
||
|
|
|
||
|
|
if "`docomb'"=="yes" & `numcats' == 2 {
|
||
|
|
di in r "Test requires at least 3 dependent categories."
|
||
|
|
}
|
||
|
|
else if "`docomb'"=="yes" {
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** Wald tests for combining alternatives `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: All coefficients except intercepts associated " /*
|
||
|
|
*/ "with a given pair"
|
||
|
|
di in g /*
|
||
|
|
*/ " of alternatives are 0 (i.e., alternatives can be combined)."
|
||
|
|
di `smcl' _newline in g %17s "Alternatives tested" _col(20) "`vline'" /*
|
||
|
|
*/ _col(26) "chi2" _col(33) "df" _col(38) "P>chi2"
|
||
|
|
di `smcl' in g _dup(19) "`dash'" "`plussgn'" _dup(24) "`dash'"
|
||
|
|
|
||
|
|
tokenize "`catvals'"
|
||
|
|
qui version 9: estimates restore _X
|
||
|
|
|
||
|
|
* cycle through all pairs of outcomes
|
||
|
|
local count1 = 1
|
||
|
|
while `count1' <= (`numcats'-1) {
|
||
|
|
local count2 = `count1' + 1
|
||
|
|
while `count2' <= `numcats' {
|
||
|
|
if "``count1''"=="`basecat'" {
|
||
|
|
quietly test [``count2'']
|
||
|
|
}
|
||
|
|
else if "``count2''"=="`basecat'" {
|
||
|
|
quietly test [``count1'']
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
quietly test [``count2''=``count1'']
|
||
|
|
}
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
local numrow = `numrow' + 1
|
||
|
|
local s1`numrow' : word `count1' of `catnms8'
|
||
|
|
local s2`numrow' : word `count2' of `catnms8'
|
||
|
|
if `pval' == . { scalar `pval' = -9999 }
|
||
|
|
mat `nxtrow' = ``count1'', ``count2'', /*
|
||
|
|
*/ `chisq', `df', `pval'
|
||
|
|
mat roweq `nxtrow' = "`s1`numrow''"
|
||
|
|
mat rownames `nxtrow' = "`s2`numrow''"
|
||
|
|
mat `matcomb' = nullmat(`matcomb') \ `nxtrow'
|
||
|
|
local count2 = `count2' + 1
|
||
|
|
}
|
||
|
|
local count1 = `count1' + 1
|
||
|
|
} /* while `count1' <= `numcats' */
|
||
|
|
|
||
|
|
mat colnames `matcomb' = cat1 cat2 chi2 df p
|
||
|
|
local countto = rowsof(`matcomb')
|
||
|
|
local count = 1
|
||
|
|
while `count' <= `countto' {
|
||
|
|
scalar `chisq' = `matcomb'[`count', 3]
|
||
|
|
scalar `df' = `matcomb'[`count', 4]
|
||
|
|
scalar `pval' = `matcomb'[`count', 5]
|
||
|
|
if `pval' == -9999 { scalar `pval' = . }
|
||
|
|
di `smcl' in y %8s "`s1`count''" _col(9) "-" %8s "`s2`count''" /*
|
||
|
|
*/ _col(20) in g "`vline'" /*
|
||
|
|
*/ _col(21) %9.3f in y `chisq' /*
|
||
|
|
*/ _col(30) %5.0f `df' /*
|
||
|
|
*/ _col(39) %4.3f `pval'
|
||
|
|
local count = `count' + 1
|
||
|
|
}
|
||
|
|
di `smcl' in g _dup(19) "`dash'" "`bottomt'" _dup(24) "`dash'"
|
||
|
|
qui version 9: estimates restore _X
|
||
|
|
return matrix combine `matcomb'
|
||
|
|
} /* if "`docomb'"=="yes" */
|
||
|
|
|
||
|
|
*-> LR tests for combining categories
|
||
|
|
|
||
|
|
if "`dolrcom'"=="yes" & `numcats' == 2 {
|
||
|
|
di in r "Test requires at least 3 dependent categories."
|
||
|
|
}
|
||
|
|
else if "`dolrcom'"=="yes" {
|
||
|
|
di _newline in g /*
|
||
|
|
*/ "**** LR tests for combining alternatives `n'"
|
||
|
|
di _newline in g /*
|
||
|
|
*/ " Ho: All coefficients except intercepts associated" /*
|
||
|
|
*/ " with a given pair"
|
||
|
|
di in g /*
|
||
|
|
*/ " of alternatives are 0 (i.e., alternatives can be collapsed)."
|
||
|
|
di `smcl' _newline in g %17s "Alternatives tested" _col(20) "`vline'" /*
|
||
|
|
*/ _col(26) "chi2" _col(33) "df" _col(38) "P>chi2"
|
||
|
|
di `smcl' in g _dup(19) "`dash'" "`plussgn'" _dup(24) "`dash'"
|
||
|
|
|
||
|
|
lrtest, saving(lrc)
|
||
|
|
tokenize "`catvals'"
|
||
|
|
|
||
|
|
* cycle through all pairs of outcomes
|
||
|
|
local count1 = 1
|
||
|
|
while `count1' <= (`numcats'-1) {
|
||
|
|
local count2 = `count1'+1
|
||
|
|
while `count2' <= `numcats' {
|
||
|
|
constraint define 999 [``count1'']
|
||
|
|
qui mlogit `depvar' `rhsnam' `wtis' /*
|
||
|
|
*/ if `sample' == 1, base(``count2'') constr(999)
|
||
|
|
qui lrtest, using(lrc)
|
||
|
|
scalar `chisq' = r(chi2)
|
||
|
|
scalar `df' = r(df)
|
||
|
|
scalar `pval' = r(p)
|
||
|
|
local numrow = `numrow' + 1
|
||
|
|
local s1`numrow' : word `count1' of `catnms8'
|
||
|
|
local s2`numrow' : word `count2' of `catnms8'
|
||
|
|
if `pval' == . { scalar `pval' = -9999 }
|
||
|
|
mat `nxtrow' = ``count1'', ``count2'', `chisq', `df', `pval'
|
||
|
|
mat roweq `nxtrow' = "`s1`numrow''"
|
||
|
|
mat rownames `nxtrow' = "`s2`numrow''"
|
||
|
|
mat `matlrc' = nullmat(`matlrc') \ `nxtrow'
|
||
|
|
local count2 = `count2' + 1
|
||
|
|
}
|
||
|
|
local count1 = `count1' + 1
|
||
|
|
} /* while `count1' <= `numcats' */
|
||
|
|
|
||
|
|
mat colnames `matlrc' = cat1 cat2 chi2 df p
|
||
|
|
local countto = rowsof(`matlrc')
|
||
|
|
local count = 1
|
||
|
|
while `count' <= `countto' {
|
||
|
|
scalar `chisq' = `matlrc'[`count', 3]
|
||
|
|
scalar `df' = `matlrc'[`count', 4]
|
||
|
|
scalar `pval' = `matlrc'[`count', 5]
|
||
|
|
if `pval' == -9999 { scalar `pval' = . }
|
||
|
|
di `smcl' in y %8s "`s1`count''" _col(9) "-" %8s "`s2`count''" /*
|
||
|
|
*/ _col(20) in g "`vline'" /*
|
||
|
|
*/ _col(21) %9.3f in y `chisq' /*
|
||
|
|
*/ _col(30) %5.0f `df' /*
|
||
|
|
*/ _col(39) %4.3f `pval'
|
||
|
|
local count = `count' + 1
|
||
|
|
}
|
||
|
|
di `smcl' in g _dup(19) "`dash'" "`bottomt'" _dup(24) "`dash'"
|
||
|
|
|
||
|
|
qui version 9: estimates restore _X
|
||
|
|
return matrix lrcomb `matlrc'
|
||
|
|
} /* if "`dolrcom'"=="yes" */
|
||
|
|
|
||
|
|
qui version 9: estimates restore _X
|
||
|
|
* drop estimates stored in program
|
||
|
|
capture estimates drop _X
|
||
|
|
capture estimates drop _Xnb
|
||
|
|
capture estimates drop _Y
|
||
|
|
capture estimates drop _suest
|
||
|
|
|
||
|
|
end
|
||
|
|
exit
|
||
|
|
* version 1.6.9 09Aug2005 - change terminology for alternatives
|
||
|
|
* version 1.7.0 22Jun2006 - fix warning for hausman; use estimates restore; add suest (undocumented)
|
||
|
|
* version 1.7.1 29Jun2006 - add suest as documented
|
||
|
|
* version 1.7.2 18Aug2006 - fix mlogit program name bug
|
||
|
|
* version 1.7.4 8Dec2006 - suest bug fix
|
||
|
|
* version 1.7.5 2007-06-29 stata 10 fixes
|