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This paper can be downloaded from Demography and the Stata data file can be downloaded from within Stata using the following command.
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear
The Stata code for this page is made possible by graduate student Kanako Ishida from Department of Sociology. We thank Vincent Fu for his permission to link his article to this page and we thank Kanako Ishida for her Stata code.
Table 2 on page 154
sort hr wr by hr wr: tab he we [fweight=freq]
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = white, wr = white
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 21,802 22,939 9,175 1,171 | 55,087
HS | 19,008 90,470 43,631 9,076 | 162,185
Some college | 6,742 39,008 66,462 20,214 | 132,426
BA or more | 913 9,464 28,780 56,897 | 96,054
-------------+--------------------------------------------+----------
Total | 48,465 161,881 148,048 87,358 | 445,752
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = white, wr = black
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 25 13 18 1 | 57
HS | 21 90 83 6 | 200
Some college | 12 44 134 41 | 231
BA or more | 1 7 46 77 | 131
-------------+--------------------------------------------+----------
Total | 59 154 281 125 | 619
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = white, wr = mexican
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 163 140 69 11 | 383
HS | 173 555 288 35 | 1,051
Some college | 80 292 615 97 | 1,084
BA or more | 18 75 249 277 | 619
-------------+--------------------------------------------+----------
Total | 434 1,062 1,221 420 | 3,137
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = white, wr = japanese
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 3 4 12 0 | 19
HS | 9 37 36 17 | 99
Some college | 3 24 78 36 | 141
BA or more | 0 9 41 141 | 191
-------------+--------------------------------------------+----------
Total | 15 74 167 194 | 450
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = black, wr = white
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 90 96 51 3 | 240
HS | 108 318 164 22 | 612
Some college | 51 214 359 106 | 730
BA or more | 5 28 80 135 | 248
-------------+--------------------------------------------+----------
Total | 254 656 654 266 | 1,830
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = black, wr = black
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 1,904 1,688 1,097 139 | 4,828
HS | 1,425 5,901 3,384 664 | 11,374
Some college | 546 2,094 5,129 1,430 | 9,199
BA or more | 65 311 1,072 1,668 | 3,116
-------------+--------------------------------------------+----------
Total | 3,940 9,994 10,682 3,901 | 28,517
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = mexican, wr = white
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 181 188 76 8 | 453
HS | 139 432 265 34 | 870
Some college | 72 274 516 133 | 995
BA or more | 6 32 118 195 | 351
-------------+--------------------------------------------+----------
Total | 398 926 975 370 | 2,669
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = mexican, wr = mexican
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 958 515 186 10 | 1,669
HS | 462 968 379 44 | 1,853
Some college | 138 382 637 94 | 1,251
BA or more | 13 50 127 115 | 305
-------------+--------------------------------------------+----------
Total | 1,571 1,915 1,329 263 | 5,078
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = japanese, wr = white
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 6 6 4 0 | 16
HS | 5 24 15 4 | 48
Some college | 6 31 76 18 | 131
BA or more | 0 12 44 79 | 135
-------------+--------------------------------------------+----------
Total | 17 73 139 101 | 330
------------------------------------------------------------------------------------------------------------------------------------------------- -> hr = japanese, wr = japanese
| we
he | <HS HS Some coll BA or mor | Total
-------------+--------------------------------------------+----------
<HS | 1 1 1 1 | 4
HS | 2 15 14 6 | 37
Some college | 0 16 69 36 | 121
BA or more | 0 2 36 91 | 129
-------------+--------------------------------------------+----------
Total | 3 34 120 134 | 291
Table 3 on page 155
Part 1: Crude estimation (left column)
xi: glm freq i.hr*i.wr , fam(pois) link(log) noheader
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -5.495447 .0234242 -234.61 0.000 -5.541357 -5.449536
_Ihr_2 | -5.118059 .0194143 -263.62 0.000 -5.15611 -5.080007
_Ihr_3 | -7.208423 .0550685 -130.90 0.000 -7.316356 -7.100491
_Iwr_1 | -6.579413 .0402213 -163.58 0.000 -6.658245 -6.50058
_Iwr_2 | -4.956496 .017917 -276.64 0.000 -4.991613 -4.921379
_Iwr_3 | -6.89827 .0471642 -146.26 0.000 -6.990711 -6.80583
_IhrXwr_1_1 | 9.325597 .0468963 198.86 0.000 9.233682 9.417512
_IhrXwr_2_2 | 5.599709 .0298767 187.43 0.000 5.541152 5.658267
_IhrXwr_3_3 | 6.772508 .0932264 72.65 0.000 6.589788 6.955229
_cons | 10.23493 .0014978 6833.32 0.000 10.23199 10.23786
------------------------------------------------------------------------------
glm, eform noheader
------------------------------------------------------------------------------
| OIM
freq | IRR Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | .0041054 .0000962 -234.61 0.000 .0039212 .0042983
_Ihr_2 | .0059876 .0001162 -263.62 0.000 .0057641 .0062199
_Ihr_3 | .0007403 .0000408 -130.90 0.000 .0006646 .0008247
_Iwr_1 | .0013887 .0000559 -163.58 0.000 .0012834 .0015026
_Iwr_2 | .0070375 .0001261 -276.64 0.000 .0067947 .0072891
_Iwr_3 | .0010095 .0000476 -146.26 0.000 .0009204 .0011073
_IhrXwr_1_1 | 11221.61 526.2527 198.86 0.000 10236.16 12301.94
_IhrXwr_2_2 | 270.3478 8.077111 187.43 0.000 254.9716 286.6514
_IhrXwr_3_3 | 873.5002 81.43326 72.65 0.000 727.6266 1048.618
------------------------------------------------------------------------------
Part 2: Adjusted estimation (right column)
First row using Model 2a, second row using Model 2b and the last row using Model 1c. For parameter estimates, see the output below for each corresponding model.
Table 4. Goodness-of-Fit Chi-Square and BIC Statistics for Marriage Models.
Marriages Between Blacks and Whites
We start with some commands to set up the framework for our analyses. Command desmat will produce most of the dummy variables needed. Command showtrms after desmat shows all the dummy variables created by destmat.
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear keep if (hr ==0 | hr ==1) & (wr==0 | wr ==1) set matsize 4001a. Endogamous intermarriage model: HRWR, HEWE, HRHE, WRWE
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 39
Scale parameter = 1
Deviance = 311.1541028 (1/df) Deviance = 7.97831
Pearson = 321.0682715 (1/df) Pearson = 8.23252
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 13.43774 Log likelihood = -405.0077735 BIC = 148.9577
Notice that the BIC statistic in the above STATA output is different from the BIC statistic from Table 4, which is produced in LEM. The discrepancy is due to how the sample size is computed. The formula for computing BIC is as follows, which is the same for both LEM and Stata.
BIC = L2 − df logN
The sample size N used in LEM for computing BIC is the total number of cases, which is 476718; while the sample size N used in Stata is 64.
di e(deviance) - e(df)*log(64) /*stata*/ 148.9577
di e(deviance) - e(df)*log(476718)/*LEM*/ -198.75843
Why is there such discrepancy? This is because we use GLM and poisson family with log link for a loglinear model instead of a "true" Poisson model where the dependent variable is a count for each individual, such as number of cigarettes a person consumes each day. In a "true" Poisson model, each observation will be an individual subject and therefore the sample size will be the number of subjects. While in our loglinear model, the data is already aggregated, the number of observations is simply the number of cells. This leads glm to use the "wrong" sample size.
2a. Endogamous intermarriage model + constrained exchange parameters.
gen hrwe=hr*we
gen wrhe=wr*he
gen racehe=hr*wr*he
gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log)
Generalized linear models No. of obs = 64
Optimization : ML: Newton-Raphson Residual df = 35
Scale param = 1
Deviance = 215.7113411 (1/df) Deviance = 6.163181
Pearson = 226.0637843 (1/df) Pearson = 6.458965
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log] Standard errors : OIM
Log likelihood = -357.2863926 AIC = 12.07145 BIC = 70.15043313
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -5.429821 .0526978 -103.04 0.000 -5.533106 -5.326535
_Iwr_1 | -6.780167 .0948934 -71.45 0.000 -6.966155 -6.594179
_IhrXwr_1_1 | 9.832134 .107579 91.39 0.000 9.621283 10.04299
_Ihe_1 | -.1309031 .0096353 -13.59 0.000 -.149788 -.1120183
_Ihe_2 | -1.156483 .0134335 -86.09 0.000 -1.182812 -1.130154
_Ihe_3 | -3.129714 .0325676 -96.10 0.000 -3.193545 -3.065883
_IhrXhe_1_1 | .0762956 .0358838 2.13 0.033 .0059646 .1466266
_IhrXhe_1_2 | .3065403 .0642607 4.77 0.000 .1805917 .4324889
_IhrXhe_1_3 | -.1699658 .0945336 -1.80 0.072 -.3552482 .0153167
_Iwe_1 | .0520947 .0092221 5.65 0.000 .0340197 .0701697
_Iwe_2 | -.8427845 .0119287 -70.65 0.000 -.8661644 -.8194046
_Iwe_3 | -2.893089 .0284268 -101.77 0.000 -2.948804 -2.837373
_IwrXwe_1_1 | -.061812 .0577742 -1.07 0.285 -.1750473 .0514233
_IwrXwe_1_2 | .3325676 .1099661 3.02 0.002 .1170379 .5480973
_IwrXwe_1_3 | .3068828 .1631548 1.88 0.060 -.0128948 .6266603
_IheXwe_1_1 | 1.508791 .0118944 126.85 0.000 1.485479 1.532104
_IheXwe_1_2 | 1.668339 .0144439 115.50 0.000 1.640029 1.696648
_IheXwe_1_3 | 2.152578 .0308899 69.69 0.000 2.092035 2.213121
_IheXwe_2_1 | 1.686741 .0155812 108.25 0.000 1.656202 1.71728
_IheXwe_2_2 | 3.119687 .0169955 183.56 0.000 3.086376 3.152997
_IheXwe_2_3 | 3.983699 .0313881 126.92 0.000 3.922179 4.045218
_IheXwe_3_1 | 2.253016 .0346641 65.00 0.000 2.185075 2.320956
_IheXwe_3_2 | 4.256361 .0344928 123.40 0.000 4.188756 4.323965
_IheXwe_3_3 | 6.984883 .042874 162.92 0.000 6.900851 7.068914
hrwe | -.10477 .0310744 -3.37 0.001 -.1656746 -.0438653
wrhe | .0209414 .0513315 0.41 0.683 -.0796664 .1215492
racehe | -.3135522 .0605968 -5.17 0.000 -.4323197 -.1947848
racewe | -.0124089 .0630049 -0.20 0.844 -.1358962 .1110783
_cons | 9.984587 .0066794 1494.84 0.000 9.971496 9.997679
------------------------------------------------------------------------------
glm, eform noheader
------------------------------------------------------------------------------
| OIM
freq | IRR Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | .0043839 .000231 -103.04 0.000 .0039537 .0048609
_Iwr_1 | .0011361 .0001078 -71.45 0.000 .0009433 .0013683
_IhrXwr_1_1 | 18622.65 2003.407 91.39 0.000 15082.39 22993.92
_Ihe_1 | .8773027 .0084531 -13.59 0.000 .8608905 .8940279
_Ihe_2 | .3145906 .004226 -86.09 0.000 .3064158 .3229835
_Ihe_3 | .0437303 .0014242 -96.10 0.000 .0410262 .0466127
_IhrXhe_1_1 | 1.079282 .0387287 2.13 0.033 1.005982 1.157921
_IhrXhe_1_2 | 1.358716 .087312 4.77 0.000 1.197926 1.541088
_IhrXhe_1_3 | .8436937 .0797574 -1.80 0.072 .7009994 1.015435
_Iwe_1 | 1.053475 .0097153 5.65 0.000 1.034605 1.07269
_Iwe_2 | .4305101 .0051354 -70.65 0.000 .4205616 .440694
_Iwe_3 | .0554048 .001575 -101.77 0.000 .0524023 .0585793
_IwrXwe_1_1 | .9400596 .0543112 -1.07 0.285 .8394173 1.052768
_IwrXwe_1_2 | 1.394544 .1533526 3.02 0.002 1.124162 1.729958
_IwrXwe_1_3 | 1.359182 .221757 1.88 0.060 .987188 1.87135
_IheXwe_1_1 | 4.521263 .0537778 126.85 0.000 4.41708 4.627904
_IheXwe_1_2 | 5.30335 .0766009 115.50 0.000 5.15532 5.45563
_IheXwe_1_3 | 8.607016 .2658694 69.69 0.000 8.101383 9.144208
_IheXwe_2_1 | 5.401847 .0841674 108.25 0.000 5.239375 5.569357
_IheXwe_2_2 | 22.63929 .3847652 183.56 0.000 21.89758 23.40611
_IheXwe_2_3 | 53.71535 1.686023 126.92 0.000 50.5104 57.12366
_IheXwe_3_1 | 9.51639 .329877 65.00 0.000 8.891317 10.18541
_IheXwe_3_2 | 70.55274 2.433559 123.40 0.000 65.94071 75.48735
_IheXwe_3_3 | 1080.18 46.31163 162.92 0.000 993.1197 1174.872
hrwe | .9005317 .0279834 -3.37 0.001 .8473219 .9570829
wrhe | 1.021162 .0524177 0.41 0.683 .9234243 1.129245
racehe | .7308462 .0442869 -5.17 0.000 .6490018 .8230118
racewe | .9876677 .0622279 -0.20 0.844 .8729332 1.117482
------------------------------------------------------------------------------
di e(deviance) - e(df)*log(476718) /*LEM's BIC*/ -241.90247
3a. Endogamous intermarriage model + unconstrained exchange parameters.
To create three-way interaction terms, we use Stata program xi3 written by Michael Michell. Please visit our page on How to use xi3 for more details on how to install the program and how to use it.
xi3: glm freq i.hr*i.wr*i.we i.hr*i.wr*i.he i.he*i.we, family(poisson) link(log)
Generalized linear models No. of obs = 64
Optimization : ML: Newton-Raphson Residual df = 27
Scale param = 1
Deviance = 169.6907143 (1/df) Deviance = 6.284841
Pearson = 180.2091516 (1/df) Pearson = 6.674413
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log] Standard errors : OIM
Log likelihood = -334.2760793 AIC = 11.60238 BIC = 57.40087109
(Parameter estimates omitted)
di e(deviance) - e(df)*log(476718) /*LEM's BIC*/ -183.32566
Marriages Between Mexican Americans and Whites
set mem 20m use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear set matsize 400 keep if (hr ==0 | hr ==2) & (wr==0 | wr ==2) recode hr 2 = 1 (32 changes made) recode wr 2 = 1 (32 changes made)
1b. Endogamous intermarriage model: HRWR, HEWE, HRHE, WRWE
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 39
Scale parameter = 1
Deviance = 448.8377411 (1/df) Deviance = 11.50866
Pearson = 445.793385 (1/df) Pearson = 11.4306
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 15.66958 Log likelihood = -476.4264449 BIC = 286.6413
sum hr [fweight=freq]
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
hr | 456636 .0169654 .1291417 0 1
di e(deviance) - e(df)*log(456636) /*LEM's BIC*/ -59.396291
2b. Endogamous intermarriage model + constrained exchange parameters.
gen hrwe=hr*we gen wrhe=wr*he gen racehe=hr*wr*he gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 35
Scale parameter = 1
Deviance = 95.95679072 (1/df) Deviance = 2.741623
Pearson = 100.5568579 (1/df) Pearson = 2.873053
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 10.28081 Log likelihood = -299.9859697 BIC = -49.60412
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -4.723932 .0443958 -106.40 0.000 -4.810946 -4.636918
_Iwr_1 | -4.757309 .0436123 -109.08 0.000 -4.842787 -4.67183
_IhrXwr_1_1 | 6.371177 .0619211 102.89 0.000 6.249814 6.49254
_Ihe_1 | -.131917 .0097671 -13.51 0.000 -.1510603 -.1127738
_Ihe_2 | -1.169692 .0136908 -85.44 0.000 -1.196525 -1.142859
_Ihe_3 | -3.157377 .0331394 -95.28 0.000 -3.222329 -3.092425
_IhrXhe_1_1 | -.4064184 .0392602 -10.35 0.000 -.483367 -.3294697
_IhrXhe_1_2 | -.0959937 .055782 -1.72 0.085 -.2053243 .0133369
_IhrXhe_1_3 | -.6369555 .0777796 -8.19 0.000 -.7894007 -.4845104
_Iwe_1 | .0541684 .009324 5.81 0.000 .0358938 .072443
_Iwe_2 | -.8608856 .0122607 -70.22 0.000 -.8849161 -.8368551
_Iwe_3 | -2.916747 .0296427 -98.40 0.000 -2.974845 -2.858648
_IwrXwe_1_1 | -.4429943 .0389933 -11.36 0.000 -.5194198 -.3665687
_IwrXwe_1_2 | -.2863952 .0544694 -5.26 0.000 -.3931533 -.1796372
_IwrXwe_1_3 | -.8343325 .0746945 -11.17 0.000 -.9807309 -.687934
_IheXwe_1_1 | 1.502122 .0121293 123.84 0.000 1.478349 1.525895
_IheXwe_1_2 | 1.688167 .0148997 113.30 0.000 1.658964 1.717369
_IheXwe_1_3 | 2.173752 .0322006 67.51 0.000 2.11064 2.236864
_IheXwe_2_1 | 1.698432 .0159068 106.77 0.000 1.667255 1.729609
_IheXwe_2_2 | 3.149082 .017489 180.06 0.000 3.114804 3.18336
_IheXwe_2_3 | 4.013497 .032688 122.78 0.000 3.94943 4.077565
_IheXwe_3_1 | 2.270502 .0352518 64.41 0.000 2.20141 2.339595
_IheXwe_3_2 | 4.297774 .0351597 122.24 0.000 4.228863 4.366686
_IheXwe_3_3 | 7.03488 .0441369 159.39 0.000 6.948373 7.121387
hrwe | -.0697913 .0257694 -2.71 0.007 -.1202985 -.0192841
wrhe | .1226142 .0228997 5.35 0.000 .0777316 .1674969
racehe | -.4243734 .0389179 -10.90 0.000 -.500651 -.3480958
racewe | -.2032684 .0404785 -5.02 0.000 -.2826049 -.1239319
_cons | 9.987544 .0067179 1486.71 0.000 9.974377 10.00071
------------------------------------------------------------------------------
glm, eform noheader
------------------------------------------------------------------------------
| OIM
freq | IRR Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | .0088802 .0003942 -106.40 0.000 .0081402 .0096875
_Iwr_1 | .0085887 .0003746 -109.08 0.000 .007885 .0093551
_IhrXwr_1_1 | 584.7455 36.2081 102.89 0.000 517.9162 660.1981
_Ihe_1 | .8764137 .0085601 -13.51 0.000 .8597959 .8933528
_Ihe_2 | .3104625 .0042505 -85.44 0.000 .3022426 .3189061
_Ihe_3 | .0425372 .0014097 -95.28 0.000 .0398621 .0453917
_IhrXhe_1_1 | .6660315 .0261485 -10.35 0.000 .6167034 .719305
_IhrXhe_1_2 | .9084697 .0506762 -1.72 0.085 .8143831 1.013426
_IhrXhe_1_3 | .5289002 .0411376 -8.19 0.000 .4541169 .6159987
_Iwe_1 | 1.055662 .009843 5.81 0.000 1.036546 1.075132
_Iwe_2 | .4227875 .0051837 -70.22 0.000 .4127488 .4330703
_Iwe_3 | .0541094 .0016039 -98.40 0.000 .0510553 .0573462
_IwrXwe_1_1 | .6421109 .0250381 -11.36 0.000 .5948656 .6931085
_IwrXwe_1_2 | .7509657 .0409046 -5.26 0.000 .6749253 .8355733
_IwrXwe_1_3 | .4341642 .0324297 -11.17 0.000 .3750369 .5026134
_IheXwe_1_1 | 4.491209 .0544754 123.84 0.000 4.385698 4.599258
_IheXwe_1_2 | 5.409553 .0806008 113.30 0.000 5.253863 5.569857
_IheXwe_1_3 | 8.791209 .2830825 67.51 0.000 8.253524 9.363923
_IheXwe_2_1 | 5.46537 .0869367 106.77 0.000 5.297606 5.638447
_IheXwe_2_2 | 23.31465 .4077506 180.06 0.000 22.52901 24.12768
_IheXwe_2_3 | 55.34008 1.808959 122.78 0.000 51.90578 59.00162
_IheXwe_3_1 | 9.684264 .3413876 64.41 0.000 9.037748 10.37703
_IheXwe_3_2 | 73.53594 2.5855 122.24 0.000 68.63911 78.78211
_IheXwe_3_3 | 1135.559 50.11998 159.39 0.000 1041.454 1238.166
hrwe | .9325884 .0240323 -2.71 0.007 .8866557 .9809006
wrhe | 1.130448 .0258869 5.35 0.000 1.080833 1.182342
racehe | .6541796 .0254593 -10.90 0.000 .6061359 .7060312
racewe | .8160592 .0330329 -5.02 0.000 .7538175 .88344
------------------------------------------------------------------------------
di e(deviance) - e(df)*log(456636) /* LEM's BIC */ -360.15067
3b. Endogamous intermarriage model + unconstrained exchange parameters.
xi3: glm freq i.hr*i.wr*i.we i.hr*i.wr*i.he i.he*i.we, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 27
Scale parameter = 1
Deviance = 44.6946585 (1/df) Deviance = 1.655358
Pearson = 48.88606823 (1/df) Pearson = 1.810595
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 9.729841 Log likelihood = -274.3549035 BIC = -67.59518
di e(deviance) - e(df)*log(456636) /*LEM's BIC*/ -307.15967
Marriages Between Japanese Americans and Whites
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear set matsize 400 keep if (hr ==0 | hr ==3) & (wr==0 | wr ==3) recode hr 3 = 1 recode wr 3 = 1
1c. Endogamous intermarriage model: HRWR, HEWE, HRHE, WRWE
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 39
Scale parameter = 1
Deviance = 60.00650411 (1/df) Deviance = 1.538628
Pearson = 53.37471888 (1/df) Pearson = 1.368583
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 7.457545 Log likelihood = -213.6414248 BIC = -102.1899
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -8.261892 .2254343 -36.65 0.000 -8.703735 -7.820049
_Iwr_1 | -8.167443 .236959 -34.47 0.000 -8.631874 -7.703011
_IhrXwr_1_1 | 6.598636 .0943047 69.97 0.000 6.413802 6.78347
_Ihe_1 | -.1368579 .0099206 -13.80 0.000 -.1563019 -.1174139
_Ihe_2 | -1.173742 .0139279 -84.27 0.000 -1.20104 -1.146444
_Ihe_3 | -3.174672 .033781 -93.98 0.000 -3.240882 -3.108462
_IhrXhe_1_1 | .2757024 .2488514 1.11 0.268 -.2120373 .7634422
_IhrXhe_1_2 | 1.416096 .2332105 6.07 0.000 .9590113 1.87318
_IhrXhe_1_3 | 1.574164 .2342499 6.72 0.000 1.115043 2.033286
_Iwe_1 | .0506317 .0094567 5.35 0.000 .0320969 .0691664
_Iwe_2 | -.8652167 .0124359 -69.57 0.000 -.8895907 -.8408427
_Iwe_3 | -2.925882 .0299854 -97.58 0.000 -2.984652 -2.867111
_IwrXwe_1_1 | .5128248 .2549084 2.01 0.044 .0132134 1.012436
_IwrXwe_1_2 | 1.442905 .2437793 5.92 0.000 .9651065 1.920704
_IwrXwe_1_3 | 1.992051 .2437857 8.17 0.000 1.51424 2.469863
_IheXwe_1_1 | 1.509288 .0123705 122.01 0.000 1.485042 1.533533
_IheXwe_1_2 | 1.695627 .0151687 111.78 0.000 1.665897 1.725357
_IheXwe_1_3 | 2.186544 .0325809 67.11 0.000 2.122686 2.250401
_IheXwe_2_1 | 1.704925 .0162215 105.10 0.000 1.673131 1.736718
_IheXwe_2_2 | 3.153876 .017826 176.93 0.000 3.118938 3.188814
_IheXwe_2_3 | 4.02382 .0331132 121.52 0.000 3.958919 4.088721
_IheXwe_3_1 | 2.289947 .0359182 63.75 0.000 2.219548 2.360345
_IheXwe_3_2 | 4.31836 .0358404 120.49 0.000 4.248115 4.388606
_IheXwe_3_3 | 7.060167 .044854 157.40 0.000 6.972255 7.14808
_cons | 9.98962 .0067718 1475.18 0.000 9.976348 10.00289
------------------------------------------------------------------------------
glm, eform noheader
------------------------------------------------------------------------------
| OIM
freq | IRR Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | .0002582 .0000582 -36.65 0.000 .000166 .0004016
_Iwr_1 | .0002837 .0000672 -34.47 0.000 .0001783 .0004515
_IhrXwr_1_1 | 734.0932 69.22847 69.97 0.000 610.2094 883.1278
_Ihe_1 | .8720941 .0086517 -13.80 0.000 .8553009 .8892171
_Ihe_2 | .3092077 .0043066 -84.27 0.000 .300881 .3177647
_Ihe_3 | .0418078 .0014123 -93.98 0.000 .0391294 .0446696
_IhrXhe_1_1 | 1.317456 .3278507 1.11 0.268 .8089345 2.145649
_IhrXhe_1_2 | 4.120999 .9610603 6.07 0.000 2.609116 6.508961
_IhrXhe_1_3 | 4.826707 1.130656 6.72 0.000 3.0497 7.639146
_Iwe_1 | 1.051935 .0099478 5.35 0.000 1.032618 1.071615
_Iwe_2 | .4209603 .005235 -69.57 0.000 .4108239 .4313469
_Iwe_3 | .0536174 .0016077 -97.58 0.000 .0505571 .0568629
_IwrXwe_1_1 | 1.670002 .4256975 2.01 0.044 1.013301 2.752298
_IwrXwe_1_2 | 4.232976 1.031912 5.92 0.000 2.625067 6.825762
_IwrXwe_1_3 | 7.330557 1.787085 8.17 0.000 4.545966 11.82082
_IheXwe_1_1 | 4.523507 .0559579 122.01 0.000 4.41515 4.634523
_IheXwe_1_2 | 5.450062 .0826703 111.78 0.000 5.290416 5.614525
_IheXwe_1_3 | 8.904384 .290113 67.11 0.000 8.353548 9.491543
_IheXwe_2_1 | 5.500973 .089234 105.10 0.000 5.328828 5.678678
_IheXwe_2_2 | 23.42669 .4176035 176.93 0.000 22.62234 24.25965
_IheXwe_2_3 | 55.91429 1.851503 121.52 0.000 52.40066 59.66351
_IheXwe_3_1 | 9.874413 .3546716 63.75 0.000 9.203174 10.59461
_IheXwe_3_2 | 75.06546 2.690379 120.49 0.000 69.97335 80.52812
_IheXwe_3_3 | 1164.64 52.23876 157.40 0.000 1066.626 1271.662
------------------------------------------------------------------------------
sum hr [fweight=freq]
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
hr | 446823 .0013898 .0372543 0 1
di e(deviance) - e(df)*log(446823) -447.38029
2c. Endogamous intermarriage model + constrained exchange parameters.
gen hrwe=hr*we gen wrhe=wr*he gen racehe=hr*wr*he gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 35
Scale parameter = 1
Deviance = 35.92198293 (1/df) Deviance = 1.026342
Pearson = 31.50947232 (1/df) Pearson = .9002706
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 7.206224 Log likelihood = -201.5991642 BIC = -109.6389
di e(deviance) - e(df)*log(446823) /*LEM's BIC*/ -419.42514
3c. Endogamous intermarriage model + unconstrained exchange parameters.
xi3: glm freq i.hr*i.wr*i.we i.hr*i.wr*i.he i.he*i.we, family(poisson) link(log) notable
Generalized linear models No. of obs = 64
Optimization : ML Residual df = 27
Scale parameter = 1
Deviance = 25.92502273 (1/df) Deviance = .960186
Pearson = 23.52088654 (1/df) Pearson = .8711439
Variance function: V(u) = u [Poisson] Link function : g(u) = ln(u) [Log]
AIC = 7.300021 Log likelihood = -196.6006841 BIC = -86.36482
di e(deviance) - e(df)*log(446823)/*LEM's BIC*/ -325.34276
Table 5. Log-Odds Ratios and Odds Ratios That Blacks', Mexican Americans', and Japanese Americans' Spouses Have More Schooling Than Whites' Spouses
Column for Model 2a:
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear keep if (hr ==0 | hr ==1) & (wr==0 | wr ==1) gen hrwe=hr*we gen wrhe=wr*he gen racehe=hr*wr*he gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log) noheader
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -5.429821 .0526978 -103.04 0.000 -5.533106 -5.326535
_Iwr_1 | -6.780167 .0948934 -71.45 0.000 -6.966155 -6.594179
_IhrXwr_1_1 | 9.832134 .107579 91.39 0.000 9.621283 10.04299
_Ihe_1 | -.1309031 .0096353 -13.59 0.000 -.149788 -.1120183
_Ihe_2 | -1.156483 .0134335 -86.09 0.000 -1.182812 -1.130154
_Ihe_3 | -3.129714 .0325676 -96.10 0.000 -3.193545 -3.065883
_IhrXhe_1_1 | .0762956 .0358838 2.13 0.033 .0059646 .1466266
_IhrXhe_1_2 | .3065403 .0642607 4.77 0.000 .1805917 .4324889
_IhrXhe_1_3 | -.1699658 .0945336 -1.80 0.072 -.3552482 .0153167
_Iwe_1 | .0520947 .0092221 5.65 0.000 .0340197 .0701697
_Iwe_2 | -.8427845 .0119287 -70.65 0.000 -.8661644 -.8194046
_Iwe_3 | -2.893089 .0284268 -101.77 0.000 -2.948804 -2.837373
_IwrXwe_1_1 | -.061812 .0577742 -1.07 0.285 -.1750473 .0514233
_IwrXwe_1_2 | .3325676 .1099661 3.02 0.002 .1170379 .5480973
_IwrXwe_1_3 | .3068828 .1631548 1.88 0.060 -.0128948 .6266603
_IheXwe_1_1 | 1.508791 .0118944 126.85 0.000 1.485479 1.532104
_IheXwe_1_2 | 1.668339 .0144439 115.50 0.000 1.640029 1.696648
_IheXwe_1_3 | 2.152578 .0308899 69.69 0.000 2.092035 2.213121
_IheXwe_2_1 | 1.686741 .0155812 108.25 0.000 1.656202 1.71728
_IheXwe_2_2 | 3.119687 .0169955 183.56 0.000 3.086376 3.152997
_IheXwe_2_3 | 3.983699 .0313881 126.92 0.000 3.922179 4.045218
_IheXwe_3_1 | 2.253016 .0346641 65.00 0.000 2.185075 2.320956
_IheXwe_3_2 | 4.256361 .0344928 123.40 0.000 4.188756 4.323965
_IheXwe_3_3 | 6.984883 .042874 162.92 0.000 6.900851 7.068914
hrwe | -.10477 .0310744 -3.37 0.001 -.1656746 -.0438653
wrhe | .0209414 .0513315 0.41 0.683 -.0796664 .1215492
racehe | -.3135522 .0605968 -5.17 0.000 -.4323197 -.1947848
racewe | -.0124089 .0630049 -0.20 0.844 -.1358962 .1110783
_cons | 9.984587 .0066794 1494.84 0.000 9.971496 9.997679
------------------------------------------------------------------------------
White Husbands' Schooling: Minority Women vs. White women
lincom wrhe /*log-odds ratio*/
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .0209414 .0513315 0.41 0.683 -.0796664 .1215492
------------------------------------------------------------------------------
lincom wrhe, or /*odds ratio*/
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 1.021162 .0524178 0.41 0.683 .9234243 1.129245
------------------------------------------------------------------------------
Minority Husbands' Schooling: Minority Women vs. White women
lincom wrhe + racehe /*log-odds ratio*/
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.2926109 .0322257 -9.08 0.000 -.3557721 -.2294497
------------------------------------------------------------------------------
lincom wrhe + racehe, or
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .7463125 .0240504 -9.08 0.000 .7006323 .794971
------------------------------------------------------------------------------
White Wives' Schooling: Minority Men vs. White Men
lincom hrwe /*log-odds ratio*/
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.10477 .0310744 -3.37 0.001 -.1656746 -.0438653
------------------------------------------------------------------------------
lincom hrwe, or
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .9005317 .0279834 -3.37 0.001 .8473219 .9570829
------------------------------------------------------------------------------
Minority Wives' Schooling: Minority Men vs. White Men
lincom hrwe + racewe /*log-odds ratio*/
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.117179 .0548248 -2.14 0.033 -.2246336 -.0097243
------------------------------------------------------------------------------
lincom hrwe + racewe, or
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .889426 .0487626 -2.14 0.033 .7988088 .9903228
------------------------------------------------------------------------------
Column for Model 2b:
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear keep if (hr ==0 | hr ==2) & (wr==0 | wr ==2) recode hr 2 = 1 recode wr 2 = 1
gen hrwe=hr*we
gen wrhe=wr*he
gen racehe=hr*wr*he
gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log) noheader
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -4.723932 .0443958 -106.40 0.000 -4.810946 -4.636918
_Iwr_1 | -4.757309 .0436123 -109.08 0.000 -4.842787 -4.67183
_IhrXwr_1_1 | 6.371177 .0619211 102.89 0.000 6.249814 6.49254
_Ihe_1 | -.131917 .0097671 -13.51 0.000 -.1510603 -.1127738
_Ihe_2 | -1.169692 .0136908 -85.44 0.000 -1.196525 -1.142859
_Ihe_3 | -3.157377 .0331394 -95.28 0.000 -3.222329 -3.092425
_IhrXhe_1_1 | -.4064184 .0392602 -10.35 0.000 -.483367 -.3294697
_IhrXhe_1_2 | -.0959937 .055782 -1.72 0.085 -.2053243 .0133369
_IhrXhe_1_3 | -.6369555 .0777796 -8.19 0.000 -.7894007 -.4845104
_Iwe_1 | .0541684 .009324 5.81 0.000 .0358938 .072443
_Iwe_2 | -.8608856 .0122607 -70.22 0.000 -.8849161 -.8368551
_Iwe_3 | -2.916747 .0296427 -98.40 0.000 -2.974845 -2.858648
_IwrXwe_1_1 | -.4429943 .0389933 -11.36 0.000 -.5194198 -.3665687
_IwrXwe_1_2 | -.2863952 .0544694 -5.26 0.000 -.3931533 -.1796372
_IwrXwe_1_3 | -.8343325 .0746945 -11.17 0.000 -.9807309 -.687934
_IheXwe_1_1 | 1.502122 .0121293 123.84 0.000 1.478349 1.525895
_IheXwe_1_2 | 1.688167 .0148997 113.30 0.000 1.658964 1.717369
_IheXwe_1_3 | 2.173752 .0322006 67.51 0.000 2.11064 2.236864
_IheXwe_2_1 | 1.698432 .0159068 106.77 0.000 1.667255 1.729609
_IheXwe_2_2 | 3.149082 .017489 180.06 0.000 3.114804 3.18336
_IheXwe_2_3 | 4.013497 .032688 122.78 0.000 3.94943 4.077565
_IheXwe_3_1 | 2.270502 .0352518 64.41 0.000 2.20141 2.339595
_IheXwe_3_2 | 4.297774 .0351597 122.24 0.000 4.228863 4.366686
_IheXwe_3_3 | 7.03488 .0441369 159.39 0.000 6.948373 7.121387
hrwe | -.0697913 .0257694 -2.71 0.007 -.1202985 -.0192841
wrhe | .1226142 .0228997 5.35 0.000 .0777316 .1674969
racehe | -.4243734 .0389179 -10.90 0.000 -.500651 -.3480958
racewe | -.2032684 .0404785 -5.02 0.000 -.2826049 -.1239319
_cons | 9.987544 .0067179 1486.71 0.000 9.974377 10.00071
------------------------------------------------------------------------------
White Husbands' Schooling: Minority Women vs. White women
lincom wrhe
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .1226142 .0228997 5.35 0.000 .0777316 .1674969
------------------------------------------------------------------------------
lincom wrhe, or
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 1.130448 .0258869 5.35 0.000 1.080833 1.182342
------------------------------------------------------------------------------
Minority Husbands' Schooling: Minority Women vs. White women
lincom wrhe + racehe
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.3017592 .0315259 -9.57 0.000 -.3635487 -.2399696
------------------------------------------------------------------------------
lincom wrhe + racehe, or
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .7395161 .0233139 -9.57 0.000 .6952049 .7866517
------------------------------------------------------------------------------
White Wives' Schooling: Minority Men vs. White Men
lincom hrwe
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.0697913 .0257694 -2.71 0.007 -.1202985 -.0192841
------------------------------------------------------------------------------
lincom hrwe, or
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .9325884 .0240323 -2.71 0.007 .8866557 .9809006
------------------------------------------------------------------------------
Minority Wives' Schooling: Minority Men vs. White Men
lincom hrwe + racewe
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.2730597 .0313038 -8.72 0.000 -.334414 -.2117055
------------------------------------------------------------------------------
lincom hrwe + racewe, or
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .7610473 .0238236 -8.72 0.000 .7157574 .809203
------------------------------------------------------------------------------
Column for Model 2c:
use http://www.ats.ucla.edu/stat/stata/paperexamples/vfu/racial, clear keep if (hr ==0 | hr ==3) & (wr==0 | wr ==3) recode hr 3 = 1 recode wr 3 = 1 gen hrwe=hr*we gen wrhe=wr*he gen racehe=hr*wr*he gen racewe=hr*wr*we
xi: glm freq i.hr*i.wr i.hr*i.he i.wr*i.we i.he*i.we ///
hrwe wrhe racehe racewe, family(poisson) link(log) noheader
------------------------------------------------------------------------------
| OIM
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_Ihr_1 | -8.485538 .2496945 -33.98 0.000 -8.974931 -7.996146
_Iwr_1 | -8.442054 .2511689 -33.61 0.000 -8.934336 -7.949772
_IhrXwr_1_1 | 7.398549 .3054584 24.22 0.000 6.799862 7.997237
_Ihe_1 | -.1369038 .0099206 -13.80 0.000 -.1563478 -.1174599
_Ihe_2 | -1.173751 .0139284 -84.27 0.000 -1.20105 -1.146451
_Ihe_3 | -3.174779 .0337817 -93.98 0.000 -3.240989 -3.108568
_IhrXhe_1_1 | .2811266 .2543589 1.11 0.269 -.2174078 .779661
_IhrXhe_1_2 | 1.440017 .2575053 5.59 0.000 .9353155 1.944718
_IhrXhe_1_3 | 1.636443 .2939296 5.57 0.000 1.060352 2.212535
_Iwe_1 | .0506843 .0094566 5.36 0.000 .0321498 .0692188
_Iwe_2 | -.8648961 .0124361 -69.55 0.000 -.8892705 -.8405217
_Iwe_3 | -2.925116 .0299859 -97.55 0.000 -2.983888 -2.866345
_IwrXwe_1_1 | .3969292 .2581923 1.54 0.124 -.1091183 .9029768
_IwrXwe_1_2 | 1.200912 .2593797 4.63 0.000 .6925375 1.709287
_IwrXwe_1_3 | 1.617694 .2837991 5.70 0.000 1.061458 2.17393
_IheXwe_1_1 | 1.509252 .0123705 122.00 0.000 1.485006 1.533498
_IheXwe_1_2 | 1.695478 .0151688 111.77 0.000 1.665747 1.725208
_IheXwe_1_3 | 2.186292 .0325811 67.10 0.000 2.122434 2.25015
_IheXwe_2_1 | 1.704788 .0162217 105.09 0.000 1.672994 1.736582
_IheXwe_2_2 | 3.153413 .0178266 176.89 0.000 3.118474 3.188353
_IheXwe_2_3 | 4.023072 .0331141 121.49 0.000 3.95817 4.087975
_IheXwe_3_1 | 2.28975 .0359185 63.75 0.000 2.219352 2.360149
_IheXwe_3_2 | 4.317667 .0358411 120.47 0.000 4.24742 4.387914
_IheXwe_3_3 | 7.059044 .0448551 157.37 0.000 6.97113 7.146958
hrwe | .097635 .0752859 1.30 0.195 -.0499226 .2451927
wrhe | .2666961 .0640856 4.16 0.000 .1410907 .3923015
racehe | -.3941511 .1365262 -2.89 0.004 -.6617376 -.1265647
racewe | .0061751 .138717 0.04 0.964 -.2657053 .2780555
_cons | 9.989721 .0067716 1475.24 0.000 9.976449 10.00299
------------------------------------------------------------------------------
White Husbands' Schooling: Minority Women vs. White women
lincom wrhe
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .2666961 .0640856 4.16 0.000 .1410907 .3923015
------------------------------------------------------------------------------
lincom wrhe, or
( 1) [freq]wrhe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 1.305644 .0836729 4.16 0.000 1.151529 1.480384
------------------------------------------------------------------------------
Minority Husbands' Schooling: Minority Women vs. White women
lincom wrhe + racehe
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -.127455 .1205773 -1.06 0.290 -.3637822 .1088722
------------------------------------------------------------------------------
lincom wrhe + racehe, or
( 1) [freq]wrhe + [freq]racehe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .880333 .1061482 -1.06 0.290 .6950425 1.11502
------------------------------------------------------------------------------
White Wives' Schooling: Minority Men vs. White Men
lincom hrwe
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .097635 .0752859 1.30 0.195 -.0499226 .2451927
------------------------------------------------------------------------------
lincom hrwe, or
( 1) [freq]hrwe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 1.10256 .0830072 1.30 0.195 .951303 1.277868
------------------------------------------------------------------------------
Minority Wives' Schooling: Minority Men vs. White Men
lincom hrwe + racewe
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | .1038102 .1166502 0.89 0.374 -.12482 .3324403
------------------------------------------------------------------------------
lincom hrwe + racewe, or
( 1) [freq]hrwe + [freq]racewe = 0.0
------------------------------------------------------------------------------
freq | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | 1.10939 .1294105 0.89 0.374 .8826558 1.394367
------------------------------------------------------------------------------
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