** user=**** ** password=**** ** package=spss ** project=lis * Czech LIS 1992 : Example CAMSIS matching . * This example on the person file, change var names to use hhld file. * Occ var index is isco88, used is pocc with isco88 2 digit groups. * Czech data has employment status 0 - unknown, * 1 - self-employed, 6 - employee . get file= cz96p . * Employment status info from ptypewk. compute empst=ptypewk. recode empst (2,4,5,7=1) (1,3,6=6) (else=0). add value labels empst 0 "Unknown" 1 "Self-employed" 6 "Employee" variable label empst "Employment status". cro empst by psex. compute isco88 =-999. if (pocc > 0 ) isco88=pocc . temp. select if (pocc > 0). means tables=isco88 by empst /cells=min max count . sort cases by isco88 empst. sav out= cstemp . get file="u:/camsis/csczis96.sav". descriptives var=all. sort cases by isco88 empst. match files table=* /in=csocc /file=cstemp /in=source /by=isco88 empst. fre var=csocc source. select if (source=1). * (this removes those occbst 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=isco88 empst cgentcs siops isei . temp. select if (pocc > 0). descriptives var=isco88 empst cgentcs siops isei . temp. select if (pocc > 0 & siops > 0). descriptives var=isco88 empst cgentcs siops isei . * Quick assessment : compare values by an education recode. compute educ=peduc. recode educ (0,1=1) (2,3,4,5,6=2) (7,8,9=3) (else=-9). add value labels educ 1 "Elementary" 2 "Intermediate" 3 "Higher level" -9 "Unknown". variable label educ "education categories". fre var= educ . descriptives var= educ cgentcs siops isei . temp. select if (pocc > 0 & siops > 0 & psex=1 & educ > 0). means tables= cgentcs siops isei by educ /statistics=anova. temp. select if (pocc > 0 & siops > 0 & psex=2 & educ > 0). means tables= cgentcs siops isei by educ /statistics=anova. /* For interest here are the Eta-squared statistics with education from above: Men: CAMSIS : 0.312 SIOPS : 0.306 ISEI: 0.324 Women: CAMSIS : 0.316 SIOPS : 0.306 ISEI: 0.282 */