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Corentin Choisy
2024-06-04 11:19:21 +02:00
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Modules/ado/plus/d/dellist.ado Normal file
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program def dellist, rclass
*! NJC 1.5.0 14 December 2000
* NJC 1.4.0 6 Sept 2000
* NJC 1.3.0 6 June 2000
* NJC 1.2.0 31 Jan 2000
* NJC 1.1.0 22 Dec 1999
* NJC 1.0.0 22 Sept 1999
version 6.0
gettoken list 0 : 0, parse(",")
if "`list'" == "" | "`list'" == "," {
di in r "nothing in list"
exit 198
}
local nlist : word count `list'
syntax , [ Delete(str) Pos(numlist sort int >=-`nlist' <=`nlist') /*
*/ Exact All Global(str) Noisily ]
local nopts = ("`delete'" != "") + ("`pos'" != "")
if `nopts' != 1 {
di in r "must specify one of delete( ) and pos( )"
exit 198
}
if length("`global'") > 8 {
di in r "global name must be <=8 characters"
exit 198
}
if "`exact'" != "" & "`all'" != "" {
di in r "all option not allowed with exact option"
exit 198
}
tokenize `list'
if "`delete'" != "" {
local i = 1
while `i' <= `nlist' {
local len = length("``i''")
if `len' > 80 {
di in r "cannot handle word length > 80"
exit 498
}
local i = `i' + 1
}
tknz `delete', s(d)
local nd : word count `delete'
if "`exact'" != "" {
while "`1'" != "" {
local i = 1
local OK = 0
while `i' <= `nd' & !`OK' {
local OK = "`1'" == "`d`i''"
local i = `i' + 1
}
if !`OK' { local newlist "`newlist'`1' " }
mac shift
}
}
else {
while "`1'" != "" {
local i = 1
local OK = 0
while `i' <= `nd' {
local thisOK = /*
*/ index("`1'", "`d`i''") > 0
local OK = `OK' + `thisOK'
local i = `i' + 1
}
if "`all'" != "" { local OK = `OK' == `nd' }
if !`OK' { local newlist "`newlist'`1' " }
mac shift
}
}
}
else {
local np1 = `nlist' + 1
tknz `pos' `np1', s(p)
local np : word count `pos'
* negative indexes to positive
local i = 1
while `p`i'' < 0 {
local p`i' = `nlist' + 1 + `p`i''
local i = `i' + 1
}
local i = 1
local j = 1
while `i' <= `nlist' {
if `i' == `p`j'' { local j = `j' + 1 }
else local newlist "`newlist'``i'' "
local i = `i' + 1
}
}
if "`noisily'" != "" { di "`newlist'" }
if "`global'" != "" { global `global' "`newlist'" }
return local list `newlist'
end
program def tknz, rclass
* NJC 1.1.0 2 June 2000
version 6.0
gettoken list 0 : 0, parse(",")
syntax , Stub(str) [ * ]
tokenize `"`list'"' , `options'
local i = 1
while "``i''" != "" {
c_local `stub'`i' `"``i''"'
local i = `i' + 1
}
end

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.h listutil

108
Modules/ado/plus/d/delta.ado Normal file
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*! Delta version 1.5 - 5 March 2008
*! Jean-Benoit Hardouin
************************************************************************************************************
* DELTA: delta coefficient
* Version 1.5: March 5, 2008
*
* Historic
* Version 1 (2007-05-21): Jean-Benoit Hardouin
* Version 1.1 (2007-05-22): Jean-Benoit Hardouin /* if in and possibility to use the score*/
* Version 1.2 (2007-05-22): Jean-Benoit Hardouin /*bug when a score is missing*/
* Version 1.3 (2007-06-16): Jean-Benoit Hardouin /*change in the options*/
* Version 1.4 (2007-07-03): Jean-Benoit Hardouin /*correct a bug in the options*/
* Version 1.5 (2008-03-05): Jean-Benoit Hardouin /*correct a bug in the ci option*/
*
* Jean-benoit Hardouin, Faculty of Pharmaceutical Sciences - University of Nantes - France
* jean-benoit.hardouin@univ-nantes.fr
*
* News about this program : http://www.anaqol.org
* FreeIRT Project : http://www.freeirt.org
*
* Copyright 2007-2008 Jean-Benoit Hardouin
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
************************************************************************************************************
program define delta , rclass
version 7.0
syntax varlist(min=1 numeric) [if] [in] [,ci(integer 0) noDots MINscore(int 0) MAXscore(int 0)]
preserve
tempfile deltafile
qui save `deltafile'
if "`if'"!=""|"`in'"!="" {
qui keep `if' `in'
}
local nbitems:word count `varlist'
tokenize `varlist'
local scoremin=`minscore'
local scoremax=`maxscore'
tempvar score
if `nbitems'==1&`scoremax'==0 {
di in red "If you indicate only the score variable, you must define the {cmd:scoremax} option"
error 198
}
else if `nbitems'==1&`scoremax'!=0 {
qui gen `score'=`varlist'
}
else {
qui genscore `varlist',score(`score')
}
qui drop if `score'==.
qui count
local nbind=r(N)
if `scoremax'==0 {
qui su `score'
local scoremax=r(max)
}
tempname error
gen `error'=`score'<`scoremin'|`score'>`scoremax'
qui count if `error'==1
local err=r(N)
if `err'!=0 {
di in red "`err' individuals has(have) a score inferior to `scoremin' or superior to `scoremax'"
error 198
}
local sumsqscore=0
forvalues i=`scoremin'/`scoremax' {
qui count if `score'==`i'
local score`i'=r(N)
local sumsqscore=`sumsqscore'+`score`i''^2
}
local delta=(1+`scoremax')*(`nbind'^2-`sumsqscore')/(`nbind'^2*`scoremax')
di in green "Range of the scores : " in ye `scoremin' in gr "/" in ye `scoremax'
di in green "Number of used individuals : " in ye `nbind'
if `ci'!=0 {
bootstrap delta=r(delta), reps(`ci') nowarn noheader nolegend `dots': delta `varlist' ,minscore(`scoremin') maxscore(`scoremax')
}
else {
display in green "Delta= " in yellow %8.6f `delta'
}
return scalar delta=`delta'
qui use `deltafile',clear
restore,not
end

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{smcl}
{* 16may2007}{...}
{hline}
help for {hi:delta}{right:Jean-Benoit Hardouin}
{hline}
{title:Syntax}
{p 8 14 2}{cmd:delta} {it:varlist} [{cmd:if} {it:exp}] [{cmd:in} {it:range}] [, {cmdab:ci}({it:#}) {cmdab:nod:ots} {cmdab:min:score}({it:#}) {cmdab:max:score}({it:#})]
{title:Description}
{p 4 8 2}{cmd:delta} computes the generalized delta index of scale discrimination developed by Hankins (2007) based on the original work of Ferguson (1949). This index measures the scale's ability to distinguish between individuals.
A value of 1 indicates that the test has maximal discrimination (all possible scores occur with the same frequency) and a value of 0 means that the test has minimal discrimination (all the respondents have the same score).
A value of 0.9 results from a set of scores that is normally distributed. A value of 1 is observed if the scores follow a uniform distribution. Individuals with a missing score are omitted.
{title:Options}
{p 4 8 2}If {it:varlist} is composed of only one variable, the {cmd:delta} module considers that this variable is the score of the individuals.
{p 4 8 2}{cmd:ci}({it:#}) estimates the confidence interval by boostrap. {it:#} is the number of replications to be performed. By default, no confidence interval is calculated.
{p 4 8 2}{cmd:nodots} avoids displaying a dot for each replication (only with {cmd:ci}).
{p 4 8 2}{cmd:minscore}({it:#}) defines the minimal value of the score. By default, this value is fixed to 0.
{p 4 8 2}{cmd:maxscore}({it:#}) defines the maximal value of the score. By default, the maximal observed score is used.
{title:Output}
{p 4 8 2}{cmd:r(delta)}: Observed value of the delta index.
{title:Examples}
{p 4 8 2}{cmd: . delta itemA*}
{p 4 8 2}{cmd: . delta itemA*, ci(500) dots}
{p 4 8 2}{cmd: . delta score, scoremax(8)}
{title: References}
{p 4 8 2}Ferguson G. A. (1949) On the theory of test discrimination. {it:Psychometrika}, 14: 61-68.
{p 4 8 2}Hankins M. (2007) Questionnaire discrimination: (re)- introducting coefficient delta. {it:BMC Medical Research Methodology}, 7: 19.
{title:Author}
{p 4 8 2}Jean-Benoit Hardouin, PhD, assistant professor{p_end}
{p 4 8 2}Team of Biostatistics, Clinical Research and Subjective Measures in Health Sciences{p_end}
{p 4 8 2}University of Nantes - Faculty of Pharmaceutical Sciences{p_end}
{p 4 8 2}1, rue Gaston Veil - BP 53508{p_end}
{p 4 8 2}44035 Nantes Cedex 1 - FRANCE{p_end}
{p 4 8 2}Email:
{browse "mailto:jean-benoit.hardouin@univ-nantes.fr":jean-benoit.hardouin@univ-nantes.fr}{p_end}
{p 4 8 2}Websites {browse "http://www.anaqol.org":AnaQol}
and {browse "http://www.freeirt.org":FreeIRT}
{title:Also see}
{p 4 13 2}Online: help for {help alpha} and {help loevH} if installed.{p_end}

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program def difflist, rclass
*! NJC 1.4.0 6 June 2000
* NJC 1.3.0 31 Jan 2000
* NJC 1.2.0 22 Dec 1999
* NJC 1.1.0 21 Dec 1999
* NJC 1.0.0 14 Oct 1999
version 6.0
gettoken lists 0 : 0, parse(",")
if "`lists'" == "" | "`lists'" == "," { /* no \ */
di in r "incorrect syntax: no separator"
exit 198
}
tokenize "`lists'", parse("\")
if "`4'" != "" {
di in r "incorrect syntax: too much stuff"
exit 198
}
if "`1'" == "\" { /* list1 empty */
if "`2'" == "\" {
di in r "incorrect syntax: one \ only"
exit 198
}
local list2 "`2'" /* might be empty */
}
else if "`2'" == "\" {
local list1 "`1'"
local list2 "`3'" /* might be empty */
}
else {
di in r "incorrect syntax: what to compare?"
exit 198
}
syntax [ , Global(str) Noisily ]
if length("`global'") > 8 {
di in r "global name must be <=8 characters"
exit 198
}
* remove duplicates from `list1'
tokenize `list1'
local list1 "`1'"
mac shift
while "`1'" != "" {
local n1 : word count `list1'
local i = 1
local putin = 1
while `i' <= `n1' {
local word : word `i' of `list1'
if "`word'" == "`1'" {
local putin = 0
local i = `n1'
}
local i = `i' + 1
}
if `putin' { local list1 "`list1' `1'" }
mac shift
}
* what is in `list1' but not `list2'?
local n1 : word count `list1'
tokenize `list1'
local n2 : word count `list2'
local i = 1
while `i' <= `n1' {
local j = 1
local putin = 1
while `j' <= `n2' {
local word : word `j' of `list2'
if "`word'" == "``i''" {
local putin = 0
local j = `n2'
}
local j = `j' + 1
}
if `putin' { local newlist "`newlist' ``i''" }
local i = `i' + 1
}
if "`noisily'" != "" { di "`newlist'" }
if "`global'" != "" { global `global' "`newlist'" }
return local list `newlist'
end

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.h listutil

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*! version 2.0 : Oct1995 : Joseph Hilbe
* Dichotomous Discriminate Anaylsis
* Based on version 1, written by Hilbe 12-7-91, published: STB-5 (Jan1992)
program define discrim2
version 5.0
local varlist "req ex"
local options "Detail Graph Anova Predict Keep"
local in "opt"
local if "opt"
parse "`*'"
parse "`varlist'",parse(" ")
qui summ `1'
if (_result(6)<0 | _result(6)>1) {
noi di in red "Error: Group variable must be 0/1"
exit
}
if "`keep'"=="" {
preserve
}
qui {
dropmiss `varlist'
tempvar prob0 prob1 dummy D nvar obs obs1 obs0 c0 c1 prop D cntall
gen `cntall'=_n
local group `1'
local y "`1'"
mac shift
qui count
gen `obs' = _result(1)
count if `group'==0
gen `obs0'= _result(1)
count if `group'==1
gen `obs1'= _result(1)
tempvar c0
gen `c0' =`obs1'/`obs'
gen `c1' = -(`obs0'/`obs')
gen `prob0' = `obs1'/`obs'
gen `dummy' = `c0' if `group'==0
replace `dummy' = `c1' if `group'==1
reg `dummy' `*', noheader
global nvar = _result(3)
cap drop `dummy' `c0' `c1'
global rsquare = _result(7)
global mahala=($rsquare/(1-$rsquare))*((`obs'*(`obs'-2))/(`obs0'*`obs1'))
gen `prop' = $rsquare/$mahala
gen `D' = sqrt($mahala)
* Calc discriminant scores
local i = 1
while "``i''"!= "" {
tempvar cof`i' dis`i'
gen `cof`i'' = _b[``i'']
gen `dis`i'' = `cof`i''/`prop'
local i = `i'+1
}
* Calc main values */
local j = 1
local i = 1
tempvar konst usdfk dscorep dscore dsFp dfun
gen `usdfk'=0
gen `konst' = 0
gen `dscorep'=0
gen `dscore'=0
gen `dsFp'=0
gen `dfun'=0
while "``i''"!="" {
tempvar mean`j' mn0`j' mn1`j' mndff`j' usdf`j'
summ ``i''
gen `mean`j'' = _result(3)
summ ``i'' if `group'==0
gen `mn0`j'' = _result(3)
summ ``i'' if `group'==1
gen `mn1`j'' = _result(3)
gen `mndff`j'' = `mn0`j'' + `mn1`j''
replace `konst' = `dis`i''*`mndff`j''+`konst'
gen `usdf`i''=`dis`i''/-`D'
replace `usdfk'=`usdf`j'' * `mean`j'' + `usdfk'
replace `dscorep'=`usdf`i''*``i''
replace `dscore'=`dscore'+`dscorep'
replace `dsFp'=`dis`i''*``i''
replace `dfun'=`dfun'+`dsFp'
local i = `i'+1
local j = `j'+1
}
replace `usdfk'=`usdfk'* -1
replace `dscore'=`dscore'+`usdfk'
replace `konst'=`konst'*-.5
replace `dfun' = `dfun'+`konst'
local tsquare = $mahala*((`obs0'*`obs1')/`obs')
local F = `tsquare'*(`obs'-$nvar)/(($nvar-1)*(`obs'-2))
global cnt0 = -`D'*(`obs1'/`obs')
global cnt1 = `D'*(`obs0'/`obs')
noi di _n
noi di in gr _col(20) "Dichotomous Discriminant Analysis"
noi di " "
#delimit ;
noi di in gr "Observations = " in ye `obs'
in gr _col(50) "Obs Group 0 = " in ye %9.0g `obs0';
noi di in gr "Indep variables = " in ye $nvar
in gr _col(50) "Obs Group 1 = " in ye %9.0g `obs1';
noi di " ";
noi di in gr "Centroid 0 = " in ye %9.4f $cnt0
in gr _col(50) "R-square = " in ye %9.4f $rsquare;
noi di in gr "Centroid 1 = " in ye %9.4f $cnt1
in gr _col(50) "Mahalanobis = " in ye %9.4f $mahala;
noi di in gr "Grand Cntd = " in ye %9.4f
((`obs1'*$cnt0)+(`obs0'*$cnt1))/`obs';
noi di " ";
#delimit cr
oneway `dscore' `group'
global eigen = _result(2)/_result(4)
global ccor = sqrt(_result(2)/(_result(2)+_result(4)))
global lambda = _result(4)/(_result(2)+_result(4))
global chisq = log($lambda)* -((`obs'-($nvar+2)/2)-1)
#delimit ;
noi di in gr "Eigenvalue = " in ye %9.4f $eigen
in gr _col(50) "Wilk's Lambda = " in ye %7.4f $lambda;
noi di in gr "Canon. Corr. = " in ye %9.4f $ccor
in gr _col(50) "Chi-square = " in ye %7.4f $chisq;
noi di in gr "Eta Squared = " in ye %9.4f $ccor^2
in gr _col(50) "Sign Chi2 = " in ye %7.4f chiprob($nvar,$chisq);
#delimit cr
* DISPLAY COEFFICIENTS
noi di _n(1)
noi di in gr _col(26) "Discrim Function" _col(46) "Unstandardized"
noi di in gr _col(11) /*
*/ "Variable" _col(28) "Coefficients" _col(48) "Coefficients"
noi di in gr _col(11) _dup(49) "-"
local i=1
while "``i''"!="" {
noi di in gr _col(11) "``i''" in ye _col(28) %9.4f `dis`i'' /*
*/ _col(51) %9.4f `usdf`i''
local i = `i'+1
}
noi di in gr _col(11) "constant" in ye _col(28) %9.4f `konst' /*
*/ _col(51) %9.4f `usdfk'
tempvar lprob grpred cell
gen `lprob' = 1/(1+exp(`dfun'))
gen `grpred' = 1 if `lprob'>=0.5
replace `grpred' = 0 if `lprob'<0.5
gen `cell' = 1
summ `cell' if `group'==0 & `lprob'<0.5
local aa=_result(2)
summ `cell' if `group'==0 & `lprob'>=0.5
local bb=_result(2)
summ `cell' if `group'==1 & `lprob'<0.5
local cc=_result(2)
summ `cell' if `group'==1 & `lprob'>=0.5
local dd=_result(2)
local tot = `aa'+`bb'+`cc'+`dd'
* CONFUSION MATRIX AND RELATED STATS OPTION
if "`predict'" !="" {
noi di _n " "
noi di in gr _col(25) "----- Predicted -----"
noi di in gr _col(13) "Actual | Group 0 Group 1 | Total"
noi di in gr _col(13) "---------+" _dup(26) "-" "+--------"
noi di in gr _col(13) "Group 0 |" in ye _col(26) %6.0g `aa' /*
*/ _col(40) %6.0g `bb' in gr _col(49) "|" in ye _col(52) %6.0g `aa'+`bb'
noi di in gr _col(13) "Group 1 |" in ye _col(26) %6.0g `cc' /*
*/ _col(40) %6.0g `dd' in gr _col(49) "|" in ye _col(52) %6.0g `cc'+`dd'
noi di in gr _col(13) "---------+" _dup(26) "-" "+--------"
noi di in gr _col(13) "Total |" in ye _col(26) %6.0g `aa'+`cc' /*
*/ _col(40) %6.0g `bb'+`dd' in gr _col(49) "|" in ye _col(52) /*
*/ %6.0g `tot'
noi di in gr _col(13) "---------+" _dup(26) "-" "+--------"
noi di " "
noi di in gr _col(21) "Correctly predicted = " in ye /*
*/ %6.2f ((`aa'+`dd')/`tot')*100 " %"
noi di in gr _col(21) "Model sensitivity = " in ye /*
*/ %6.2f (`aa'/(`aa'+`bb'))*100 " %"
noi di in gr _col(21) "Model specificity = " in ye /*
*/ %6.2f (`dd'/(`cc'+`dd'))*100 " %"
noi di in gr _col(21) "False positive = " in ye /*
*/ %6.2f (`cc'/(`aa'+`cc'))*100 " %"
noi di in gr _col(21) "False negative = " in ye /*
*/ %6.2f (`bb'/(`bb'+`dd'))*100 " %"
}
* ANOVA OPTION
if "`anova'"!="" {
noi di _n(1)
noi di in gr _col(18) "Discriminant Scores v Group Variable"
noi oneway `dscore' `group'
}
* GRAPH OPTION
if "`graph'"!="" {
tempvar lnp lnm
gen `lnp'=`lprob' if (`lprob'>=0.5 & `group'==1) | /*
*/ (`lprob'<0.5 & `group'==0)
gen `lnm'=`lprob' if `lnp'==.
lab var `lnp' "Classified"
lab var `lnm' "Misclassified"
lab var `dfun' "Discriminant Index"
noi gr `lnp' `lnm' `dfun', s(.p) xlab ylab(.1,.3,.4,.5,.6,.7,.9) /*
*/ border yline(.5) ti(" Probability of Classification")
cap drop `lnp' `lnm'
}
* INDIVIDUAL CLASSIFICATION STATISTICS OPTION: SAVES WITH SAVE OPTION
if "`detail'"!="" {
cap drop PRED DscScore DscIndex LnProb1 Group DIFF
sort `cntall'
noi di _n(2)
gen PRED=`grpred'
gen DscScore = `dscore'
gen DscIndex = `dfun'
gen LnProb1 = `lprob'
gen Group = `group'
compress Group PRED
gen str2 DIFF = " *" if `group'!=PRED
format DIFF %2s
format DscIndex DscScore LnProb1 %9.4f
noi di in gr " PRED = Predicted Group DIFF = Misclassification"
noi di in gr " LnProb1 = Probability Gr 1 DscScore = Discriminant Score"
noi di in gr " DscIndex = Discriminant Index"
noi di in gr _dup(63) "-"
di " "
noi l `y' PRED DIFF LnProb1 DscIndex DscScore, nol
}
global S_E_var $nvar
global S_E_obs `obs'
global S_E_ob0 `obs0'
global S_E_ob1 `obs1'
global S_E_cn0 $cnt0
global S_E_cn1 $cnt1
global S_E_cng ((`obs1'*$cnt0)+(`obs0'*$cnt1))/`obs'
global S_E_r2 $rsquare
global S_E_mah $mahala
global S_E_eig $eigen
global S_E_lam $lamda
global S_E_cc $ccor
global S_E_chi $chisq
global S_E_e2 $ccor^2
global S_E_cmd "discrim"
}
if "`keep'"!="" {
noi di _n in bl " Caution: data changed in memory"
}
if "`keep'"=="" {
restore
}
end
* DROP MISSING VALUES
capture program drop dropmiss
program define dropmiss
local varlist "req ex"
parse "`*'"
parse "`varlist'", parse(" ")
local i= 1
while "``i''"!="" {
drop if ``i''==.
local i=`i'+1
}
end

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.-
help for ^discrim^ (STB-x)
.-
Dichotomous Discriminant Analysis
---------------------------------
^discrim^ grpvar [varlist] [^, p^redict^ a^nova^ g^raph^ d^etail^ k^eep]
Description
-----------
^discrim^ allows the user to perform a discriminant analysis on a Bernoulli
distributed response of grouping variable (1/0).
Output includes table with the following statistics and their global
designation for post-estimation use when applicable:
1. Observations [S_E_obs] 2. Independent vars [S_E_var]
3. Obs: group==0 [S_E_ob0] 4. Obs: group==1 [S_E_ob1]
5. Centroid 0 [S_E_cn0] 6. Centroid 1 [S_E_cn1]
7. Grand centroid [S_E_cng] 8. R-square [S_E_r2]
9. Mahalanobis [S_E_mah] 10. Eigenvalue [S_E_eig]
11. Canon. Correl [S_E_cc] 12. Eta squared [S_E_e2]
13. Wilk's lambda [S_E_lam] 14. Chi-square [S_E_chi]
Output also includes a table displaying both the Discriminant Function and
Unstandardized Coefficients.
Cases in which a variable has a missing value are dropped from estimation.
The ^keep^ command does not restore such cases to active memory.
Options
-------
^predict^ provides a confusion matrix of actual vs predicted group cell
counts. Also included is a listing of the following percentages:
1. Correctly predicted 2. Model sensitivity
3. Model specificity 4. False Positive
5. False Negative
^anova^ provides an ANOVA of discriminant scores vs the group variable.
Bartlett's test for equal variances in included.
^graph^ provides a classification graph showing correctly and incorrectly
classified cases.
^detail^ creates and lists the following for each retained case:
1. Group : actual group value
2. PRED : predicted group value
3. DIFF : a star indicating misclassified cases
4. LnProb1 : logistic probability of grouyp 1 membership
5. DscIndex : discriminant index
6. DscScore : discriminant score
^keep^ allows the user to keep the variables created in the Detail option.
The data set in memory is altered, so care must be taken when saving the
resultant file to disk.
Examples
--------
. ^discrim foreign price mpg length^
. ^discrim foreign price mpg length, p a gr d^
. ^discrim foreign price mpg length, detail keep^
Also see
--------
STB-5 (Jan1992): smv3 - Hilbe, "Regression based dichotomous discriminant
analysis".
Selvin, Steve (1995, 1996) "Practical Biostatistical Methods", Chap 6.
Explanation and use of the 1st version of the ^discrim^ command.
Additional help
---------------
Joseph Hilbe, Dept of Sociology, Arizona State University
Email: atjmh@@asuvm.inre.asu.edu

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*! 1.0.1 14mar2000 jw/ics
program define dropvars
version 6
while "`1'" != "" {
capture drop `1'
if _rc {
local nodropv "`nodropv' `1'"
}
mac shift
}
if "`nodropv'" != "" {
di in gr "Unable to drop" in ye "`nodropv'"
}
end

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.-
help for ^dropvars^ [jw] Mar 14, 2000
.-
Drop variables
--------------
^dropvars^ list
Description
-----------
^dropvars^ drops the variables that match the varlist specifications in list.
In contrast with ^drop^, ^dropvars^ allows terms in list that do not match
any variables; ^drop^ complain if any variable does not exist, and then
drops nothing.
^dropvars list^ is equivalent to
^for any list : capture drop X^
Example
-------
. ^dropvars a* b*^
drop all variables that start with either a or b.
Also see
--------
Manual: ^[R] drop^
On-line: help for @drop@