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# st: too good to be true : lr test in mlogit?

 From John Litfiba To statalist@hsphsun2.harvard.edu Subject st: too good to be true : lr test in mlogit? Date Fri, 13 May 2011 10:12:34 +0200

```Dear all (again)

I was wondering if my results seems too good to be true. I run a
multinomial logit for yvar (caterical variable with 4 possible values)
and I obtain the following results :

1) It is normal to obtain such a negative log likelihood when we use
very large sample, right ? (n=2 millions here)
2) if the association (for example given by tabulation) show that
there is strong association between yvar and xvar1 then it is
plausible to obtain this fastastic LR statistic of... 140000 ??

mlogit yvar xvar1 xvar2

Iteration 0:   log likelihood = -1953742.5
Iteration 1:   log likelihood =   -1900152
Iteration 2:   log likelihood = -1883338.4
Iteration 3:   log likelihood =   -1880317
Iteration 4:   log likelihood = -1880312.7
Iteration 5:   log likelihood = -1880312.7

Multinomial logistic regression                   Number of obs   =    2227058
LR chi2(6)      =  146859.43
Prob > chi2     =     0.0000
Log likelihood = -1880312.7                       Pseudo R2       =     0.0376

------------------------------------------------------------------------------
order |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
yvar0 |  (base outcome)
-------------+----------------------------------------------------------------
yvar1           |
xvar1 |  -2.137044   .0104876  -203.77   0.000    -2.157599   -2.116489
xvar2|  -.0099444   .0001223   -81.32   0.000    -.0101841   -.0097047
_cons |   1.708873   .0125759   135.88   0.000     1.684225    1.733522
-------------+----------------------------------------------------------------
yvar2         |
xvar1 |   .8905294   .0734511    12.12   0.000     .7465678    1.034491
xvar2 |  -.0087927   .0003393   -25.92   0.000    -.0094576   -.0081277
_cons |  -3.672227   .0758592   -48.41   0.000    -3.820908   -3.523546
-------------+----------------------------------------------------------------
yvar3          |
xvar1 |  -3.826486   .0113315  -337.69   0.000    -3.848695   -3.804276
xvar2 |  -.0054125   .0002488   -21.76   0.000    -.0059002   -.0049249
_cons |   1.244583   .0180673    68.89   0.000     1.209171    1.279994
------------------------------------------------------------------------------
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```