(gauss) run c:\dara\maketemp.gss (gauss) run c:\dara\cntrepl1.gss @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with white offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_asn Parameter Estimate S.E. Het-con S.E. beta0 -2.4873 0.8818 0.7034 pw80 1.7932 1.2560 1.0703 chngasn -20.2947 21.3588 17.6853 xasn 50.5804 27.7967 25.4436 log-likelihood = -23.0902 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_asn Parameter Estimate S.E. Het-con S.E. beta0 -2.3151 0.9547 0.7199 pw80 1.5692 1.3839 1.1244 chngasn -22.9500 24.8541 18.2654 xasn 53.8630 32.4927 26.3548 gamma0 -0.5490 0.9220 0.6358 log-likelihood = -21.7406 n = 51 @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with unknown offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_asn Parameter Estimate S.E. Het-con S.E. beta0 -0.2275 0.3172 0.3758 pw80 0.5117 0.5387 0.6297 chngasn -9.0254 9.2922 7.2743 xasn 31.4683 12.8288 10.8728 log-likelihood = -4.5461 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_asn Parameter Estimate S.E. Het-con S.E. beta0 -0.2353 0.3764 0.3709 pw80 0.5081 0.6383 0.6390 chngasn -6.8238 10.5638 7.0175 xasn 28.8542 14.8014 10.6482 gamma0 -0.6868 0.7197 0.6212 log-likelihood = -2.7430 n = 51 @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with white offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_lat Parameter Estimate S.E. Het-con S.E. beta0 -1.0328 0.5034 0.6843 pw80 1.8819 0.7121 0.9497 chnghsp -15.4318 8.9865 15.7293 xhsp 33.3626 12.9888 20.0109 log-likelihood = -10.0976 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_lat Parameter Estimate S.E. Het-con S.E. beta0 -1.0569 0.6955 0.8335 pw80 1.8464 0.9459 0.9939 chnghsp -9.0483 12.1517 17.1740 xhsp 26.2616 17.0748 20.8409 gamma0 -0.0696 0.5311 0.5628 log-likelihood = -4.5033 n = 51 @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with unknown offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_lat Parameter Estimate S.E. Het-con S.E. beta0 -0.2098 0.3665 0.4286 pw80 1.5202 0.5321 0.6283 chnghsp 0.3509 5.5334 11.9835 xhsp 10.9753 8.5531 17.2546 log-likelihood = 27.8372 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_lat Parameter Estimate S.E. Het-con S.E. beta0 -0.0775 0.4477 0.3948 pw80 1.3524 0.6590 0.5919 chnghsp -5.2460 7.4690 8.7705 xhsp 18.6950 11.8009 13.1107 gamma0 0.0382 0.4772 0.6513 log-likelihood = 36.6074 n = 51 @-----------------------------------------------@ @ Anti-Black Incidents @ @ with white offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_blk Parameter Estimate S.E. Het-con S.E. beta0 0.2581 0.1752 0.2602 pw80 2.2919 0.2382 0.3660 chngblk -1.2234 2.6223 3.0363 xblk 9.3633 4.0306 4.3331 log-likelihood = 303.8158 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: w_blk Parameter Estimate S.E. Het-con S.E. beta0 0.2647 0.2521 0.2386 pw80 2.2808 0.3421 0.3381 chngblk -2.1897 3.7107 3.0788 xblk 10.6347 5.6936 4.3861 gamma0 0.2551 0.3833 0.3247 log-likelihood = 314.6474 n = 51 @-----------------------------------------------@ @ Anti-Black Incidents @ @ with unknown offenders @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_blk Parameter Estimate S.E. Het-con S.E. beta0 1.3927 0.1065 0.1919 pw80 1.5368 0.1557 0.3056 chngblk -6.0380 1.3441 1.9222 xblk 21.7807 2.1242 2.2201 log-likelihood = 1132.8235 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: uk_blk Parameter Estimate S.E. Het-con S.E. beta0 1.4536 0.1994 0.1832 pw80 1.4519 0.2898 0.2864 chngblk -5.8650 2.5401 2.1361 xblk 21.3502 4.1441 2.7712 gamma0 0.9897 0.2881 0.2448 log-likelihood = 1165.1584 n = 51 @-----------------------------------------------@ @ Anti-Asian Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newahc Parameter Estimate S.E. Het-con S.E. beta0 -0.1771 0.3256 0.3569 pw80 -0.0290 0.5716 0.6129 ratio_a 0.2505 0.5659 0.6399 ratioax 1.8867 0.7079 0.7388 log-likelihood = 43.5856 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newahc Parameter Estimate S.E. Het-con S.E. beta0 -0.0761 0.4194 0.3640 pw80 0.0781 0.7455 0.6247 ratio_a 0.1092 0.7563 0.7439 ratioax 1.8072 0.9724 0.8668 gamma0 0.0870 0.4755 0.4382 log-likelihood = 49.6037 n = 51 @-----------------------------------------------@ @ Anti-Latino Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newlhc Parameter Estimate S.E. Het-con S.E. beta0 0.3933 0.2869 0.4299 pw80 0.9912 0.4691 0.6744 ratio_h -0.5260 0.9563 1.3325 ratiohx 2.6847 1.2527 1.5572 log-likelihood = 157.5678 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newlhc Parameter Estimate S.E. Het-con S.E. beta0 0.2947 0.4545 0.4326 pw80 1.2008 0.7478 0.6304 ratio_h -0.2999 1.5052 1.4705 ratiohx 2.2433 2.0207 1.7933 gamma0 0.7483 0.3572 0.3887 log-likelihood = 178.5433 n = 51 @-----------------------------------------------@ @ Anti-Black Incidents @ @ with white or unknown offenders @ @ alternative measures of ethnic change @ @-----------------------------------------------@ =============================================================================== Poisson Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newbhc Parameter Estimate S.E. Het-con S.E. beta0 1.9115 0.0858 0.1769 pw80 1.4219 0.1323 0.2635 ratio_b -1.1622 0.4244 0.9854 ratiobx 2.5342 0.4984 1.2532 log-likelihood = 2001.5564 n = 51 =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: newbhc Parameter Estimate S.E. Het-con S.E. beta0 1.9698 0.1912 0.1649 pw80 1.3738 0.2921 0.2397 ratio_b -1.2379 0.9451 0.8311 ratiobx 2.5080 1.1251 1.0784 gamma0 1.6161 0.2509 0.2238 log-likelihood = 2079.1241 n = 51 @-----------------------------------------------@ @ Asian-White Marriages @ @-----------------------------------------------@ =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: wnhanh Parameter Estimate S.E. Het-con S.E. beta0 -10.2285 4.0245 5.1749 pw80 2.4413 0.3915 0.3484 chngasn 20.3318 5.7824 3.4304 xasn -24.5069 8.8140 6.2520 lntot90 1.1353 0.3395 0.4362 gamma0 3.7504 0.2179 0.2243 log-likelihood = 25237.9441 n = 51 @-----------------------------------------------@ @ Latino-White Marriages @ @-----------------------------------------------@ =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: wnhhis Parameter Estimate S.E. Het-con S.E. beta0 -4.0269 2.7605 2.8911 pw80 2.6287 0.2812 0.2340 chnghsp 6.5408 2.8494 2.5007 xhsp -7.8242 4.9133 3.8076 lntot90 0.7196 0.2343 0.2434 gamma0 4.3076 0.2302 0.1764 log-likelihood = 123790.4694 n = 51 @-----------------------------------------------@ @ Black-White Marriages @ @-----------------------------------------------@ =============================================================================== Negative Binomial Regression Model =============================================================================== COUNT Version 4.0.1 3/09/1998 11:10 am =============================================================================== Data Set: temp ------------------------------------------------------------------------------- Dependent Variable: bnhwnh Parameter Estimate S.E. Het-con S.E. beta0 -5.6939 4.1480 4.9155 pw80 -0.1787 0.2408 0.2229 chngblk 3.6513 1.8371 1.2711 xblk -1.1891 3.8260 1.8582 lntot90 0.8742 0.3511 0.4165 gamma0 3.4133 0.2131 0.2307 log-likelihood = 18361.4398 n = 51 (gauss)