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# st: clogit:determining number of observations for each level of a categorical variable

 From Daniel Herbert Opi To statalist@hsphsun2.harvard.edu Subject st: clogit:determining number of observations for each level of a categorical variable Date Mon, 27 Jun 2011 15:36:35 +0100

```Dear Statalist,
I am new to Statalist and had a question that I hope I can get some
input on. I am carrying out conditional logistic regression-clogit
(example below) on a case control study where each case has been
matched to a control to look at the effect of several independent
categorical variables (xyz and abc in my example) on a dependent
variable of disease outcome (disease). The output in stata shows the
total number of observations used for the analysis (326 in this case)
but I was wondering whether there is a way of determining the number
of observations used for each level of the independent categorical
variables (xyz and abc) since I can already tell some observations (65
in this case) have been dropped because of having all positive or
negative outcomes.

. clogit disease i.xyz i.abc, strata (set1) or
note: 65 groups (65 obs) dropped because of all positive or
all negative outcomes.
Iteration 0:   log likelihood = -107.72902
Iteration 1:   log likelihood = -107.64854
Iteration 2:   log likelihood = -107.64852
Iteration 3:   log likelihood = -107.64852
Conditional (fixed-effects) logistic regression   Number of obs   =        326
LR chi2(4)      =      10.67
Prob > chi2     =     0.0305
Log likelihood = -107.64852                       Pseudo R2       =     0.0472
------------------------------------------------------------------------------
disease | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
xyz |
1  |   2.380791    .951431     2.17   0.030      1.08782    5.210571
2  |    2.73225    1.09711     2.50   0.012     1.243735    6.002232
|
abc |
1  |   .5346201   .1450661    -2.31   0.021     .3141063    .9099424
2  |   .9274642   .3857671    -0.18   0.856     .4104408    2.095771
------------------------------------------------------------------------------

Regards

Daniel

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```