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


From   Daniel Herbert Opi <[email protected]>
To   [email protected]
Subject   Re: st: clogit:determining number of observations for each level of a categorical variable
Date   Tue, 28 Jun 2011 11:18:10 +0100

Dear Jacob and Nick,

Thank you very much for the response. That was very helpful.

Regards

Daniel

On Mon, Jun 27, 2011 at 7:10 PM, Nick Cox <[email protected]> wrote:
> -findit distinct- also finds other and more recent sources, including
>
>
> FAQ     . . . . . . . . . . . . . .  Calculating the number of distinct values
>        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J. Cox
>        9/06    How do I calculate the number of distinct
>                values seen so far?
>                http://www.stata.com/support/faqs/data/distinctvalues.html
>
> FAQ     . . . . . . . . .  Counting distinct strings across a set of variables
>        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J. Cox
>        7/04    How do I count the number of distinct strings
>                across a set of variables?
>                http://www.stata.com/support/faqs/data/distinctstrings.html
>
> FAQ     . . . . . . . . . . . . . . . . . . .  Number of distinct observations
>        . . . . . . . . . . . . . . . . . . . . . . . N. J. Cox and G. Longton
>        4/02    How do I compute the number of distinct observations?
>                http://www.stata.com/support/faqs/data/distinct.html
>
> SJ-8-4  dm0042  . . . . . . . . . . . .  Speaking Stata: Distinct observations
>        (help distinct if installed)  . . . . . .  N. J. Cox and G. M. Longton
>        Q4/08   SJ 8(4):557--568
>        shows how to answer questions about distinct observations
>        from first principles; provides a convenience command
>
> Nick
> [email protected]
>
> Jacob Fowles
> Sent: 27 June 2011 17:47
>
> I have used the user written command by Longton and Cox named
> "distinct" for this exact purpose ("ssc install distinct").  There is
> also a Stata FAQ on
> this subject that provides some other strategies:
>
> http://www.stata.com/support/faqs/data/distinct.html
>
> On Mon, Jun 27, 2011 at 9:36 AM, Daniel Herbert Opi
>
>
>> 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
>> ------------------------------------------------------------------------------
>
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