** user=**** ** password=**** ** package=spss ** project=lis set printback=listing . * SPSS Sweden LIS 1995 : Example CAMSIS matching . get file= sw95p . * Current occ unit (nykmin's)=pocc. compute nykmin=-999 . if (pocc >= 0 ) nykmin=pocc . * employment status info from plfs and ptypewk, here use former. * Mostly though have to treat as missing. compute empst=0. if (plfs=4) empst=1. if (plfs=1 | plfs=2 | plfs=3) empst=2. add value label empst 0 "Unknown employment status" 1 "Self-employed" 2 "Employee" . variable label empst "Employment status". cro empst by psex. * Key indexing variables are nykmin and empst. sort cases by nykmin empst. temp. select if (pocc > 0). means tables=nykmin by empst . sav out= cstemp . get file="u:/camsis/csswis95.sav" . descriptives var=all. sort cases by nykmin empst. match files table=* /in=csocc /file=cstemp /in=source /by=nykmin empst. fre var=csocc source. cro csocc by source. select if (source=1). * (this removes those CAMSIS nykmin by empst values which are not * represented in the LIS sample). cro source by psex. * Current values are within gender. * also can make a cross-gender CAMSIS variable : . compute cgentcs=-999. if (psex=1) cgentcs=mcam . if (psex=2) cgentcs=fcam . descriptives var=nykmin empst cgentcs . temp. select if (pocc > 0). descriptives var= nykmin empst cgentcs . * We only match CAMSIS scores through the minor group * averages to about 78% of valid occs for Sweden 1995. * Quick assessment: compare values by an education recode. * some recode of education . compute educ=peduc. recode educ (1,2=1) (3,4=2) (5,6,7=3) (else=-9). add value labels educ 1 "Elementary" 2 "Intermediate" 3 "Secondary or higher" . variable label educ "education categories". fre var=educ . temp. select if (pocc > 0). descriptives var= educ cgentcs . temp. select if (pocc > 0 & psex=1 & educ > 0). means tables= cgentcs by educ /statistics=anova. temp. select if (pocc > 0 & psex=2 & educ > 0). means tables= cgentcs by educ /statistics=anova. /* For interest here are the Eta-squared statistics with education from above: Men: CAMSIS : 0.285 Women: CAMSIS : 0.244 */