Multiple-Population Repeated Measures with PROC CATMOD

This script illustrates the use of the CATMOD procedure to analyze binary responses (0 or 1) recorded during four successive trials on subjects from three different groups. It performs a repeated measures analysis by first fitting a saturated model on marginal probabilities, then a model with nested effects.

Data Analysis

Type : INTERNAL_CREATION

Data is generated directly within the script via the DATALINES statement. The INPUT statement uses the '@@' operator to read multiple observations per line.

1 Code Block

DATA STEP Data

Explanation :
Creation of the 'group' dataset. Variables a, b, c, d represent responses to 4 trials. 'Group' is the group identifier and 'wt' is the weighting (frequency). The '@@' operator allows reading multiple observations on a single physical line.

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1	DATA group;
2	INPUT a b c d Group wt @code_sas_json/8_SAS_Intro_ReadFile_MultiCol_@@.json;
3	DATALINES;
4	1 1 1 1 2 2 0 0 0 0 2 2 0 0 1 0 1 2 0 0 1 0 2 2
5	0 0 0 1 1 4 0 0 0 1 2 1 0 0 0 1 3 3 1 0 0 1 2 1
6	0 0 1 1 1 1 0 0 1 1 2 2 0 0 1 1 3 5 0 1 0 0 1 4
7	0 1 0 0 2 1 0 1 0 1 2 1 0 1 0 1 3 2 0 1 1 0 3 1
8	1 0 0 0 1 3 1 0 0 0 2 1 0 1 1 1 2 1 0 1 1 1 3 2
9	1 0 1 0 1 1 1 0 1 1 2 1 1 0 1 1 3 2
10	;

2 Code Block

PROC CATMOD

Explanation :
Execution of PROC CATMOD. The first part fits a saturated model for repeated measures (defined by 'repeated Trial 4') on marginal probabilities. The second MODEL statement (interactive mode) tests a specific structure where the effect of trials is nested within group 3.

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1	title 'Multiple-Population Repeated Measures';
2	PROC CATMOD DATA=group;
3	weight wt;
4	response marginals;
5	model abcd=Group _response_ Group_response_
6	/ freq;
7	repeated Trial 4;
8	title2 'Saturated Model';
9	RUN;
10
11	model abc*d=Group _response_(Group=3)
12	/ noprofile noparm design;
13	title2 'Trial Nested within Group 3';
14	QUIT;

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