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From | "Michael N. Mitchell" <Michael.Norman.Mitchell@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: logit or probit : why one row is missing S.E., z-score, and confidence interval?? |
Date | Tue, 25 Jan 2011 23:12:00 -0800 |
Greetings I think the problem may be suggested by the message > Note: 9 failures and 0 successes completely determined.In such a case, I would try -exlogistic- command (for exact logistic regression) and see if that might provide more appropriate results.
I hope this helps, Michael N. Mitchell Data Management Using Stata - http://www.stata.com/bookstore/dmus.html A Visual Guide to Stata Graphics - http://www.stata.com/bookstore/vgsg.html Stata tidbit of the week - http://www.MichaelNormanMitchell.com On 2011-01-25 9.17 PM, Hong, Sounman wrote:
All my variables (dependent and independent) are binary. I ran a regression and I found there is no multicollinearity. Everything looked good. But if I run a logit or probit then, as you can see below, some stats (standard error, z-score) do not show for one variable. I wonder why??? Can someone help me, please? . reg depvar varI varR varW varAA varRvarW varIvarR, r Linear regression Number of obs = 102 F( 6, 95) = 4.96 Prob> F = 0.0002 R-squared = 0.1885 Root MSE = .39009 ------------------------------------------------------------------------------ | Robust depvar | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- varI | .4132157 .1222138 3.38 0.001 .1705906 .6558407 varR | .5424289 .1517043 3.58 0.001 .2412578 .8436 varW | .1506902 .1567265 0.96 0.339 -.1604513 .4618317 varAA | .2461644 .0670512 3.67 0.000 .1130509 .3792779 varRvarW | -.3753536 .1827751 -2.05 0.043 -.7382082 -.0124991 varIvarR | -.5573226 .1643252 -3.39 0.001 -.8835492 -.2310959 _cons | -.2919213 .1258739 -2.32 0.023 -.5418126 -.0420301 ------------------------------------------------------------------------------ . probit depvar varI varR varW varAA varRvarW varIvarR, r Probit regression Number of obs = 102 Wald chi2(5) = . Prob> chi2 = . Log pseudolikelihood = -41.68023 Pseudo R2 = 0.2344 ------------------------------------------------------------------------------ | Robust depvar | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- varI | 6.200518 . . . . . varR | 6.766806 .4989077 13.56 0.000 5.788965 7.744647 varW | .4070662 .6244081 0.65 0.514 -.8167511 1.630884 varAA | 1.436624 .5493662 2.62 0.009 .3598866 2.513362 varRvarW | -1.470836 .7256594 -2.03 0.043 -2.893103 -.0485701 varIvarR | -6.964342 .3732943 -18.66 0.000 -7.695985 -6.232699 _cons | -7.856409 .6625587 -11.86 0.000 -9.155 -6.557818 ------------------------------------------------------------------------------ Note: 9 failures and 0 successes completely determined. . logit depvar varI varR varW varAA varRvarW varIvarR, or Logistic regression Number of obs = 102 LR chi2(6) = 25.21 Prob> chi2 = 0.0003 Log likelihood = -41.837978 Pseudo R2 = 0.2315 ------------------------------------------------------------------------------ depvar | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- varI | 9.48e+07 8.16e+07 21.35 0.000 1.76e+07 5.12e+08 varR | 2.69e+08 . . . . . varW | 2.136371 2.232017 0.73 0.467 .2756554 16.5572 varAA | 14.17273 15.6 2.41 0.016 1.638821 122.5676 varRvarW | .0790781 .1006545 -1.99 0.046 .0065254 .9583132 varIvarR | 2.99e-09 2.16e-09 -27.10 0.000 7.22e-10 1.24e-08 ------------------------------------------------------------------------------ Note: 9 failures and 0 successes completely determined. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/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/statalist/faq * http://www.ats.ucla.edu/stat/stata/