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| From | William Buchanan <william@williambuchanan.net> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| Subject | Re: st: gologit2 interaction |
| Date | Sun, 1 Sep 2013 16:10:25 -0500 |
Although I thank you for following the protocol of showing your input and output, you still have yet to acknowledge where you downloaded the package from. In general I think many folks here would tell you to start off with a simpler model. Is the coefficient for the interaction term of particular interest or are you trying to increase the model fit by including additional parameters? How is your outcome distributed? No one other than you can tell you whether or not you can use that in your study. HTH, Billy Sent from my iPhone On Sep 1, 2013, at 14:59, lan zhang <cat1984@126.com> wrote: > the raw model: > gologit2 ma2 z2targetcrossus z2usinl z2chcross z2chdo woe jv rd network repoffice z2age unique z2location z2chsenior z2reve >> nue z2mconcentration z2var65 > > Generalized Ordered Logit Estimates Number of obs = 230 > LR chi2(48) = 131.44 > Prob > chi2 = 0.0000 > Log likelihood = -190.91867 Pseudo R2 = 0.2561 > > ---------------------------------------------------------------------------------- > ma2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] > -----------------+---------------------------------------------------------------- > 0 | > z2targetcrossus | -.0173887 .1668386 -0.10 0.917 -.3443863 .3096089 > z2usinl | -.2492047 .1905918 -1.31 0.191 -.6227578 .1243484 > z2chcross | .103573 .1520177 0.68 0.496 -.1943763 .4015223 > z2chdo | -.0393117 .1750591 -0.22 0.822 -.3824213 .3037979 > woe | -.4751755 .6626994 -0.72 0.473 -1.774043 .8236915 > jv | -1.083191 .7963511 -1.36 0.174 -2.644011 .4776286 > rd | .9039168 .4271417 2.12 0.034 .0667344 1.741099 > network | 1.410567 .9212801 1.53 0.126 -.3951092 3.216242 > repoffice | -1.001058 .4313348 -2.32 0.020 -1.846458 -.1556568 > z2age | .1168134 .1774538 0.66 0.510 -.2309898 .4646165 > unique | .6194533 .3772757 1.64 0.101 -.1199934 1.3589 > z2location | .1114399 .1717018 0.65 0.516 -.2250895 .4479693 > z2chsenior | .0730508 .1674231 0.44 0.663 -.2550924 .401194 > z2revenue | -.014403 .165149 -0.09 0.931 -.3380891 .3092831 > z2mconcentration | -.2459377 .1718248 -1.43 0.152 -.5827081 .0908327 > z2var65 | .2098376 .1512144 1.39 0.165 -.0865371 .5062123 > _cons | -.4365704 .6758439 -0.65 0.518 -1.7612 .8880593 > -----------------+---------------------------------------------------------------- > 1 | > z2targetcrossus | .5896636 .3993497 1.48 0.140 -.1930474 1.372375 > z2usinl | -5.757507 3.010157 -1.91 0.056 -11.65731 .1422915 > z2chcross | .3443698 .8501671 0.41 0.685 -1.321927 2.010667 > z2chdo | .0274867 .3531697 0.08 0.938 -.6647132 .7196866 > woe | -.1374271 .8539173 -0.16 0.872 -1.811074 1.53622 > jv | -1.625354 1.073093 -1.51 0.130 -3.728578 .47787 > rd | .2289301 .5789769 0.40 0.693 -.9058436 1.363704 > network | .9461952 1.146079 0.83 0.409 -1.300079 3.192469 > repoffice | .1904672 .6567114 0.29 0.772 -1.096663 1.477598 > z2age | .3646071 .2886476 1.26 0.207 -.2011317 .930346 > unique | .1462646 .6053367 0.24 0.809 -1.040174 1.332703 > z2location | .3362546 .2857039 1.18 0.239 -.2237147 .896224 > z2chsenior | -.6377379 .2899929 -2.20 0.028 -1.206114 -.0693622 > z2revenue | .4384878 .2596045 1.69 0.091 -.0703277 .9473032 > z2mconcentration | -.3356207 .3044584 -1.10 0.270 -.9323481 .2611067 > z2var65 | .680389 .2555405 2.66 0.008 .1795389 1.181239 > _cons | -3.852209 1.534456 -2.51 0.012 -6.859688 -.8447304 > -----------------+---------------------------------------------------------------- > 2 | > z2targetcrossus | -1.859479 .9033436 -2.06 0.040 -3.63 -.0889579 > z2usinl | 29.60616 10.01538 2.96 0.003 9.97637 49.23595 > z2chcross | -6.148175 2.31656 -2.65 0.008 -10.68855 -1.607802 > z2chdo | -2.199313 .9065691 -2.43 0.015 -3.976156 -.4224705 > woe | 4.507415 2.227588 2.02 0.043 .1414227 8.873408 > jv | 20.13766 566.9975 0.04 0.972 -1091.157 1131.432 > rd | -3.677817 1.353729 -2.72 0.007 -6.331076 -1.024557 > network | -20.33935 566.9957 -0.04 0.971 -1131.631 1090.952 > repoffice | 5.012434 2.120188 2.36 0.018 .8569423 9.167927 > z2age | .5531285 .5823306 0.95 0.342 -.5882184 1.694475 > unique | -7.34904 2.068999 -3.55 0.000 -11.4042 -3.293877 > z2location | 3.362253 .9824052 3.42 0.001 1.436774 5.287732 > z2chsenior | .4177627 .4609106 0.91 0.365 -.4856056 1.321131 > z2revenue | .8860638 .4915586 1.80 0.071 -.0773735 1.849501 > z2mconcentration | 1.555764 .692565 2.25 0.025 .1983613 2.913166 > z2var65 | -.5325391 .556961 -0.96 0.339 -1.624163 .5590843 > _cons | 8.84202 3.903878 2.26 0.024 1.19056 16.49348 > ---------------------------------------------------------------------------------- > model with interaction: > . gologit2 ma2 z2targetcrossus z2usinl z2chcross z2chdo woe jv rd network repoffice z2age unique z2location z2chsenior z2reve >> nue z2mconcentration z2var65 z2targetrd > > Generalized Ordered Logit Estimates Number of obs = 230 > LR chi2(51) = 148.17 > Prob > chi2 = 0.0000 > Log likelihood = -182.55401 Pseudo R2 = 0.2887 > > ---------------------------------------------------------------------------------- > ma2 | Coef. Std. Err. z P>|z| [95% Conf. Interval] > -----------------+---------------------------------------------------------------- > 0 | > z2targetcrossus | -.1086327 .1786952 -0.61 0.543 -.4588687 .2416034 > z2usinl | -.224747 .1906251 -1.18 0.238 -.5983653 .1488713 > z2chcross | .1182669 .153385 0.77 0.441 -.1823621 .418896 > z2chdo | -.1046159 .1873578 -0.56 0.577 -.4718305 .2625987 > woe | -.531372 .6963073 -0.76 0.445 -1.896109 .8333653 > jv | -1.16429 .8444907 -1.38 0.168 -2.819462 .490881 > rd | -.2352473 .6686808 -0.35 0.725 -1.545838 1.075343 > network | 1.654026 .9829236 1.68 0.092 -.2724686 3.580521 > repoffice | -1.165368 .4452497 -2.62 0.009 -2.038042 -.2926951 > z2age | .0913011 .1810404 0.50 0.614 -.2635316 .4461339 > unique | .6011205 .3888613 1.55 0.122 -.1610336 1.363275 > z2location | .1073559 .1764745 0.61 0.543 -.2385278 .4532396 > z2chsenior | .111229 .1726965 0.64 0.520 -.2272498 .4497079 > z2revenue | -.0261089 .1675079 -0.16 0.876 -.3544183 .3022005 > z2mconcentration | -.2419455 .176234 -1.37 0.170 -.5873579 .1034668 > z2var65 | .2004429 .1538167 1.30 0.193 -.1010322 .5019181 > z2targetrd | .5360898 .2728751 1.96 0.049 .0012645 1.070915 > _cons | -.1930397 .7108041 -0.27 0.786 -1.58619 1.200111 > -----------------+---------------------------------------------------------------- > 1 | > z2targetcrossus | .9581676 .4375794 2.19 0.029 .1005277 1.815808 > z2usinl | -7.478695 3.056712 -2.45 0.014 -13.46974 -1.48765 > z2chcross | .183797 1.136537 0.16 0.872 -2.043775 2.411369 > z2chdo | .0680997 .3728366 0.18 0.855 -.6626467 .7988461 > woe | -.0332427 .8441079 -0.04 0.969 -1.687664 1.621178 > jv | -2.196873 1.394514 -1.58 0.115 -4.930071 .5363247 > rd | 2.356204 1.012723 2.33 0.020 .3713034 4.341105 > network | .5403172 1.4498 0.37 0.709 -2.301238 3.381872 > repoffice | 1.179 .7543806 1.56 0.118 -.2995585 2.657559 > z2age | .3700746 .3043611 1.22 0.224 -.2264622 .9666115 > unique | .0186732 .6888141 0.03 0.978 -1.331378 1.368724 > z2location | .4302243 .3273268 1.31 0.189 -.2113244 1.071773 > z2chsenior | -.9859917 .3561425 -2.77 0.006 -1.684018 -.2879651 > z2revenue | .5751533 .2707602 2.12 0.034 .0444731 1.105833 > z2mconcentration | -.287354 .334713 -0.86 0.391 -.9433795 .3686715 > z2var65 | .7992744 .2936887 2.72 0.006 .2236551 1.374894 > z2targetrd | -.7707145 .3850767 -2.00 0.045 -1.525451 -.0159781 > _cons | -4.906128 1.712643 -2.86 0.004 -8.262847 -1.54941 > -----------------+---------------------------------------------------------------- > 2 | > z2targetcrossus | -1.40224 .940126 -1.49 0.136 -3.244853 .440373 > z2usinl | 27.85302 9.856849 2.83 0.005 8.533951 47.17209 > z2chcross | -5.887844 2.251756 -2.61 0.009 -10.3012 -1.474484 > z2chdo | -2.131811 .9187053 -2.32 0.020 -3.93244 -.3311814 > woe | 4.412064 2.322375 1.90 0.057 -.1397075 8.963836 > jv | 19.98229 628.5635 0.03 0.975 -1211.98 1251.944 > rd | -2.206978 1.697812 -1.30 0.194 -5.534629 1.120673 > network | -20.38483 628.5619 -0.03 0.974 -1252.343 1211.574 > repoffice | 5.196042 2.137634 2.43 0.015 1.006356 9.385727 > z2age | .7685141 .6105997 1.26 0.208 -.4282392 1.965267 > unique | -8.068043 2.163387 -3.73 0.000 -12.3082 -3.827882 > z2location | 3.371957 1.005542 3.35 0.001 1.401131 5.342782 > z2chsenior | .3486575 .5132131 0.68 0.497 -.6572217 1.354537 > z2revenue | .9434554 .5230482 1.80 0.071 -.0817001 1.968611 > z2mconcentration | 1.711886 .6913372 2.48 0.013 .3568901 3.066882 > z2var65 | -.4395993 .5783425 -0.76 0.447 -1.57313 .6939311 > z2targetrd | -.6754823 .5818942 -1.16 0.246 -1.815974 .4650093 > _cons | 8.627572 3.824513 2.26 0.024 1.131665 16.12348 > ---------------------------------------------------------------------------------- > > my question is: variable like z2targetcrossus is not significant in the raw model, but the interaction z2targetrd=z2targetcrossus*rd is significant. > How could this happen? > can i still use this result in my study? > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/