Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: RE: logit or probit : why one row is missing S.E., z-score, and confidence interval??


From   Nick Cox <n.j.cox@durham.ac.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: logit or probit : why one row is missing S.E., z-score, and confidence interval??
Date   Wed, 26 Jan 2011 12:10:43 +0000

You've got one clue to difficulties: 

"Note: 9 failures and 0 successes completely determined." 

Thus see how the data look in terms of cross-combinations of -depvar-, -varI-, -varR-. 

I don't see that your regression results indicate lack of multicollinearity: you'd need to consider that more directly. 

Nick 
n.j.cox@durham.ac.uk 

Hong, Sounman

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/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index