OUTDIST= Output Data Set

The LOGISTIC Procedure

OUTDIST= Output Data Set

The OUTDIST= data set contains every exact conditional distribution necessary to process the EXACT statement. For example, the following statements create one distribution for the x1 parameter and another for the x2 parameters, and produces the data set dist shown in the following table:

   proc logistic;
      class x2 / param=ref;
      model y=x1 x2;
      exact x1 x2 / outdist=dist;
   proc print data=dist;
   run;

Obs	x1	x20	x21	Count	Score	Prob
1	.	0	0	3	5.81151	0.03333
2	.	0	1	15	1.66031	0.16667
3	.	0	2	9	3.12728	0.10000
4	.	1	0	15	1.46523	0.16667
5	.	1	1	18	0.21675	0.20000
6	.	1	2	6	4.58644	0.06667
7	.	2	0	19	1.61869	0.21111
8	.	2	1	2	3.27293	0.02222
9	.	3	0	3	6.27189	0.03333
10	2	.	.	6	3.03030	0.12000
11	3	.	.	12	0.75758	0.24000
12	4	.	.	11	0.00000	0.22000
13	5	.	.	18	0.75758	0.36000
14	6	.	.	3	3.03030	0.06000

The first nine observations in the dist data set contain a permutation distribution for the parameters of the x2 effect (hence the values for the x1 parameter are missing), and the remaining five observations are for the x1 parameter. If a joint distribution was created, there would be observations with values for both the x1 and x2 parameters. For CLASS variables, the corresponding parameters in the dist data set are identified by concatenating the variable name with the appropriate classification level.

The data set contains the possible sufficient statistics of the parameters for the effects specified in the EXACT statement, and the Count variable contains the number of different responses that yield these statistics. For example, there were six possible response vectors y for which the product y'x1 was equal to 2, and for which y'x20, y'x21, and y'1 were equal to their actual observed values (displayed in the "Sufficient Statistics" table). When hypothesis tests are performed on the parameters, the Prob variable contains the probability of obtaining that statistic (which is just the count divided by the total count), and the Score variable contains the score for that statistic. For more information, see the "EXACT Statement Examples" section.

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