Computed theoretical power for N=100 and N=200 scenarios
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237
Modules/ado/plus/p/praccum.ado
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237
Modules/ado/plus/p/praccum.ado
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*! version 1.7.2 2Nov2005 ztp ztnb
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* version 1.7.1 13Apr2005
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* version 1.7.0 27Mar2004 slogit
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* version 1.6.4 27Apr2001 change to work with forvalues
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* version 1.6.3 17Mar2001
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capture program drop praccum
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program define praccum
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version 6
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tempname newmat
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*=> classify each valid type of model
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if "`e(cmd)'"=="cloglog" { local io = "typical binary" }
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if "`e(cmd)'"=="cnreg" { local io = "typical regress" }
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if "`e(cmd)'"=="fit" { local io = "typical regress" }
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if "`e(cmd)'"=="gologit" { local io = "typical mlogit" }
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if "`e(cmd)'"=="intreg" { local io = "typical regress" }
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if "`e(cmd)'"=="logistic" { local io = "typical none" }
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if "`e(cmd)'"=="logit" { local io = "typical binary" }
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if "`e(cmd)'"=="mlogit" { local io = "typical mlogit" }
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if "`e(cmd)'"=="nbreg" { local io = "typical count" }
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if "`e(cmd)'"=="ologit" { local io = "typical ordered" }
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if "`e(cmd)'"=="oprobit" { local io = "typical ordered" }
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if "`e(cmd)'"=="poisson" { local io = "typical count" }
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if "`e(cmd)'"=="probit" { local io = "typical binary" }
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if "`e(cmd)'"=="regress" { local io = "typical regress" }
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if "`e(cmd)'"=="slogit" { local io = "typical ordered" }
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if "`e(cmd)'"=="tobit" { local io = "typical regress" }
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if "`e(cmd)'"=="zinb" { local io = "twoeq count" }
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if "`e(cmd)'"=="zip" { local io = "twoeq count" }
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if "`e(cmd)'"=="ztp" { local io = "typical count" }
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if "`e(cmd)'"=="ztnb" { local io = "typical count" }
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if "`io'"=="" {
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di
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di in y "praccum" in r /*
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*/ " does not work for the last type of model estimated."
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exit
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}
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local input : word 1 of `io' /* input routine to _pepred */
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local output : word 2 of `io' /* output routine */
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*=> decode specified input
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syntax [, Saving(string) Using(string) GENerate(string) XIS(string)]
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*truncate generate root if more than five characters
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if "`generate'" ~= "" {
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local gen = substr("`generate'",1,29)
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cap version 7
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if _rc != 0 { local gen = substr("`gen'",1,5) }
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version 6.0
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}
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if "`output'" == "ordered" | "`output'" == "mlogit" {
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tempname values
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mat `values' = r(values)
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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local k`count' = `values'[`count',1]
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if `k`count'' < -9 | `k`count'' > 99 | int(`k`count'')!=`k`count'' {
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di in red "category values must be integers between -9 and 99"
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exit 198
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}
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if `k`count'' < 0 {
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local k`count' = abs(`k`count'')
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local k`count' = "_`k`count''"
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}
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local count = `count' + 1
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}
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}
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if "`xis'"!="" {
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tempname results
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if "`output'" == "regress" {
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matrix `results' = ( `xis' , r(xb) )
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}
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if "`output'" == "binary" {
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* grab output from binary model
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matrix `results' = ( `xis' , r(p0) , r(p1) )
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}
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if "`output'" == "ordered" | "`output'" == "mlogit" {
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tempname probs newprob
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mat `probs' = r(probs)
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local outcms = rowsof(r(probs))
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matrix `results' = `xis'
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local count = 1
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while `count' <= `outcms' {
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matrix `newprob' = `probs'[`count', 1]
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matrix `results' = `results' , `newprob'
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local count = `count' + 1
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}
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}
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if "`output'" == "count" {
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tempname probs newprob values
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mat `values' = r(values)
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mat `probs' = r(probs)
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local outcms = rowsof(r(probs))
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local rmu = r(mu)
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matrix `results' = `xis', `rmu'
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local count = 1
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while `count' <= `outcms' {
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matrix `newprob' = `probs'[`count', 1]
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matrix `results' = `results' , `newprob'
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local count = `count' + 1
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}
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}
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if "`input'" == "twoeq" & "`output'"=="count" {
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tempname az
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matrix `az' = r(always0)
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matrix `results' = `results' , `az'
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}
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*=> saving is the initial run
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if "`saving'" ~= "" { mat `saving' = `results' }
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if "`using'" ~= "" {
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cap mat list `using'
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if _rc ~= 0 {
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mat `using' = `results'
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* OLD SYNTAX: error if `using' matrix does not already exist
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* di in r "matrix `using' does not exist"
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* exit 111
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}
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else { mat `using' = (`using') \ (`results') }
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}
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}
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*=> generates creates the new variables
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if "`gen'" ~= "" {
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if "`output'" == "regress" {
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local columns = "`gen'x `gen'xb"
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}
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if "`output'" == "binary" {
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local columns = "`gen'x `gen'p0 `gen'p1"
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}
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if "`output'" == "ordered" | "`output'" == "mlogit" {
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local columns "`gen'x"
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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local columns "`columns' `gen'p`k`count''"
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local count = `count' + 1
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}
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}
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if "`output'" == "count" {
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local columns "`gen'x `gen'mu"
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local outcms = rowsof(r(probs))
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local count = 0
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while `count' <= (`outcms'-1) {
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local columns "`columns' `gen'p`count'"
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local count = `count' + 1
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}
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if "`input'"=="twoeq" {
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local columns "`columns' `gen'inf"
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}
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}
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* create new variables
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matrix colnames `using' = `columns'
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svmat `using', names(col)
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*=> label variables
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label variable `gen'x "value of x"
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if "`output'" == "regress" {
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label variable `gen'xb "value of xb"
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}
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if "`output'" == "binary" {
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label variable `gen'p0 "Pr(0)"
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label variable `gen'p1 "Pr(1)"
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}
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if "`output'" == "ordered" {
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tempname values
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mat `values' = r(values)
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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local count2 = `count'
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label variable `gen'p`k`count'' "Pr(`k`count'')"
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local count = `count' + 1
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}
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}
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if "`output'" == "mlogit" {
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tempname values
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mat `values' = r(values)
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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local value = `values'[`count', 1]
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local count2 = `count'
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label variable `gen'p`k`count'' "Pr(`k`count'')"
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local count = `count' + 1
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}
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}
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if "`output'" == "count" {
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tempname values
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mat `values' = r(values)
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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local value = `values'[`count', 1]
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label variable `gen'p`value' "Pr(`value')"
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local count = `count' + 1
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}
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if "`input'"=="twoeq" {
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label variable `gen'inf "Pr(always0)"
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}
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}
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*=> for ordered and count variables, generate cumulative counts
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if "`output'" == "ordered" {
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local outcms = rowsof(r(probs))
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local count = 1
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while `count' <= `outcms' {
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qui egen `gen's`k`count'' = rsum(`gen'p`k1'-`gen'p`k`count'') if `gen'p`k1'~=.
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local cumul = "`cumul'`gen's`k`count'' "
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label variable `gen's`k`count'' "Pr(<=`k`count'')"
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local count = `count' + 1
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}
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}
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if "`output'" == "count" {
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local outcms = rowsof(r(probs))
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local count = 0
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while `count' <= (`outcms'-1) {
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qui egen `gen's`count' = rsum(`gen'p0-`gen'p`count') if `gen'p0~=.
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local cumul = "`cumul'`gen's`count' "
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label variable `gen's`count' "Pr(<=`count')"
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local count = `count' + 1
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}
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}
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*=> display new variables
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di _n in g "New variables created by" in w " praccum" in y ":"
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sum `columns' `cumul'
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} /* generate */
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end
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