. tabi 18 20 12 \ 28 51 25 \ 14 28 9, all | col row | 1 2 3 | Total -----------+---------------------------------+---------- 1 | 18 20 12 | 50 2 | 28 51 25 | 104 3 | 14 28 9 | 51 -----------+---------------------------------+---------- Total | 60 99 46 | 205 Pearson chi2(4) = 2.9072 Pr = 0.573 likelihood-ratio chi2(4) = 2.9232 Pr = 0.571 Cramer's V = 0.0842 gamma = 0.0185 ASE = 0.101 Kendall's tau-b = 0.0116 ASE = 0.063 . rename row wife . rename col husb . list wife husb pop 1. 1 1 18 2. 1 2 20 3. 1 3 12 4. 2 1 28 5. 2 2 51 6. 2 3 25 7. 3 1 14 8. 3 2 28 9. 3 3 9 . tabulate wife [freq=pop], generate(w) wife | Freq. Percent Cum. ------------+----------------------------------- 1 | 50 24.39 24.39 2 | 104 50.73 75.12 3 | 51 24.88 100.00 ------------+----------------------------------- Total | 205 100.00 . list wife husb pop w1 w2 w3 1. 1 1 18 1 0 0 2. 1 2 20 1 0 0 3. 1 3 12 1 0 0 4. 2 1 28 0 1 0 5. 2 2 51 0 1 0 6. 2 3 25 0 1 0 7. 3 1 14 0 0 1 8. 3 2 28 0 0 1 9. 3 3 9 0 0 1 . tabulate husb [freq=pop], generate(h) husb | Freq. Percent Cum. ------------+----------------------------------- 1 | 60 29.27 29.27 2 | 99 48.29 77.56 3 | 46 22.44 100.00 ------------+----------------------------------- Total | 205 100.00 . poisson pop Iteration 0: Log Likelihood = -49.219971 Iteration 1: Log Likelihood = -47.126953 Iteration 2: Log Likelihood = -47.117981 Poisson regression Number of obs = 9 Goodness-of-fit chi2(8) = 50.589 Model chi2(0) = 0.000 Prob > chi2 = 0.0000 Prob > chi2 = . Log Likelihood = -47.118 Pseudo R2 = 0.0000 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- _cons | 3.125785 .069843 44.754 0.000 2.988896 3.262675 ------------------------------------------------------------------------------ . poisson pop w2 w3 Iteration 0: Log Likelihood = -34.733582 Iteration 1: Log Likelihood = -33.980591 Iteration 2: Log Likelihood = -33.978607 Poisson regression Number of obs = 9 Goodness-of-fit chi2(6) = 24.310 Model chi2(2) = 26.279 Prob > chi2 = 0.0005 Prob > chi2 = 0.0000 Log Likelihood = -33.979 Pseudo R2 = 0.2789 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- w2 | .732368 .1720912 4.256 0.000 .3950754 1.069661 w3 | .0198026 .1990172 0.100 0.921 -.3702639 .4098692 _cons | 2.813411 .1414214 19.894 0.000 2.53623 3.090591 ------------------------------------------------------------------------------ . poisson pop h2-h3 Iteration 0: Log Likelihood = -37.327026 Iteration 1: Log Likelihood = -36.426575 Iteration 2: Log Likelihood = -36.424469 Poisson regression Number of obs = 9 Goodness-of-fit chi2(6) = 29.202 Model chi2(2) = 21.387 Prob > chi2 = 0.0001 Prob > chi2 = 0.0000 Log Likelihood = -36.424 Pseudo R2 = 0.2270 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- h2 | .5007752 .1636083 3.061 0.002 .1801088 .8214416 h3 | -.2657033 .195974 -1.356 0.175 -.6498052 .1183986 _cons | 2.995732 .1290994 23.205 0.000 2.742702 3.248763 ------------------------------------------------------------------------------ . poisson pop w2-w3 h2-h3 Iteration 0: Log Likelihood = -23.391937 Iteration 1: Log Likelihood = -23.285126 Iteration 2: Log Likelihood = -23.285095 Poisson regression Number of obs = 9 Goodness-of-fit chi2(4) = 2.923 Model chi2(4) = 47.666 Prob > chi2 = 0.5708 Prob > chi2 = 0.0000 Log Likelihood = -23.285 Pseudo R2 = 0.5058 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- w2 | .732368 .1720912 4.256 0.000 .3950754 1.069661 w3 | .0198027 .1990172 0.100 0.921 -.3702638 .4098692 h2 | .5007753 .1636083 3.061 0.002 .1801089 .8214417 h3 | -.2657032 .195974 -1.356 0.175 -.6498051 .1183987 _cons | 2.683358 .1782936 15.050 0.000 2.333908 3.032807 ------------------------------------------------------------------------------ . xi: poisson pop i.wife i.husb i.wife Iwife_1-3 (naturally coded; Iwife_1 omitted) i.husb Ihusb_1-3 (naturally coded; Ihusb_1 omitted) Iteration 0: Log Likelihood = -23.391937 Iteration 1: Log Likelihood = -23.285126 Iteration 2: Log Likelihood = -23.285095 Poisson regression Number of obs = 9 Goodness-of-fit chi2(4) = 2.923 Model chi2(4) = 47.666 Prob > chi2 = 0.5708 Prob > chi2 = 0.0000 Log Likelihood = -23.285 Pseudo R2 = 0.5058 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- Iwife_2 | .732368 .1720912 4.256 0.000 .3950754 1.069661 Iwife_3 | .0198027 .1990172 0.100 0.921 -.3702638 .4098692 Ihusb_2 | .5007753 .1636083 3.061 0.002 .1801089 .8214417 Ihusb_3 | -.2657032 .195974 -1.356 0.175 -.6498051 .1183987 _cons | 2.683358 .1782936 15.050 0.000 2.333908 3.032807 ------------------------------------------------------------------------------ . generate rc = (wife-1)*3 + (husb-1) . xi: poisson pop i.rc i.rc Irc_0-8 (naturally coded; Irc_0 omitted) Iteration 0: Log Likelihood = -21.884888 Iteration 1: Log Likelihood = -21.823517 Iteration 2: Log Likelihood = -21.823486 Poisson regression Number of obs = 9 Goodness-of-fit chi2(0) = 0.000 Model chi2(8) = 50.589 Prob > chi2 = . Prob > chi2 = 0.0000 Log Likelihood = -21.823 Pseudo R2 = 0.5368 ------------------------------------------------------------------------------ pop | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---------+-------------------------------------------------------------------- Irc_1 | .1053605 .3248931 0.324 0.746 -.5314184 .7421394 Irc_2 | -.4054651 .372678 -1.088 0.277 -1.135901 .3249703 Irc_3 | .4418328 .302109 1.462 0.144 -.1502899 1.033956 Irc_4 | 1.041454 .2741594 3.799 0.000 .5041112 1.578796 Irc_5 | .3285041 .3091206 1.063 0.288 -.2773612 .9343694 Irc_6 | -.2513144 .3563483 -0.705 0.481 -.9497443 .4471155 Irc_7 | .4418328 .302109 1.462 0.144 -.1502899 1.033956 Irc_8 | -.6931472 .4082483 -1.698 0.090 -1.493299 .1070048 _cons | 2.890372 .2357023 12.263 0.000 2.428404 3.35234 ------------------------------------------------------------------------------