/* Replication Program: Green, Strolovitch, and Wong (in press) "Defended Neighborhoods, Integration, and Racially Motivated Crime" American Journal of Sociology Poisson & Negative binomial regression analyses: I. ALTERNATIVE MEASURES OF HATE CRIME II. ALTERNATIVE MEASURES OF ETHNIC CHANGE III. INTERRACIAL MARRIAGE: # of occurrences */ @-----------------------------------------------@ @ Read in GAUSS Count Module and Gauss dataset @ @-----------------------------------------------@ library count; #include count.ext; countset; print " @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with white offenders @ @-----------------------------------------------@"; dep1 = { w_asn }; ind1 = { pw80,chngasn,xasn }; _cnstart=2; @ poisson regression used with robust standard errors @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with unknown offenders @ @-----------------------------------------------@"; dep1 = { uk_asn }; ind1 = { pw80,chngasn,xasn }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with white offenders @ @-----------------------------------------------@"; dep1 = { w_lat }; ind1 = { pw80,chnghsp,xhsp }; _cnstart=2; @ poisson regression used with robust standard errors @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with unknown offenders @ @-----------------------------------------------@"; dep1 = { uk_lat }; ind1 = { pw80,chnghsp,xhsp }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Black Incidents @ @ with white offenders @ @-----------------------------------------------@"; dep1 = { w_blk }; ind1 = { pw80,chngblk,xblk }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Black Incidents @ @ with unknown offenders @ @-----------------------------------------------@"; dep1 = { uk_blk }; ind1 = { pw80,chngblk,xblk }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@"; dep1 = { newahc }; ind1 = { pw80,ratio_a,ratioax }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@"; dep1 = { newlhc }; ind1 = { pw80,ratio_h,ratiohx }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Anti-Black Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@"; dep1 = { newbhc }; ind1 = { pw80,ratio_b,ratiobx }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); screen on; call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ screen off; { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); print " @-----------------------------------------------@ @ Asian-White Marriages @ @-----------------------------------------------@"; dep1 = { wnhanh }; ind1 = { pw80,chngasn,xasn,lntot90 }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); _max_GradTol=.001; print " @-----------------------------------------------@ @ Latino-White Marriages @ @-----------------------------------------------@"; dep1 = { wnhhis }; ind1 = { pw80,chnghsp,xhsp,lntot90 }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik); _max_GradTol=.0001; print " @-----------------------------------------------@ @ Black-White Marriages @ @-----------------------------------------------@"; dep1 = { bnhwnh }; ind1 = { pw80,chngblk,xblk,lntot90 }; _cnstart=2; @ poisson regression provides start values for negative binomial regression @ screen off; { b,vc,llik } = poisson("temp",dep1,ind1); call countprt(b,vc,llik); _cnsval=b|-2; @ negative binomial regression @ { b,vc,llik } = negbin("temp",dep1,ind1,0); screen on; call countprt(b,vc,llik);