/* RepeatedMonkey.sas */
title 'Primate hippocampal function: Zola-Morgan and Squire, 1990';
title2 'Covariance Structure approach to repeated measures (within-cases)';

data memory;
     infile '/folders/myfolders/monkey.data.txt' firstobs=2;
     input monkey $ treatment $ week2 week4 week8 week12 week16;
     /* Make 5 "cases" in the data set for each line in the raw data file. 
        The  output  command generates a case. */
     id = _n_;
     time = 2;   score = week2;   output;
     time = 4;   score = week4;   output;
     time = 8;   score = week8;   output;
     time = 12;  score = week12;  output;
     time = 16;  score = week16;  output;
     keep monkey treatment id time score;

proc print;

proc freq;
     tables time*treatment /norow nocol nopercent;
     tables monkey;

proc mixed cl;
     title3 'Unstructured Covariance Matrix';
     class treatment time;
     model score = treatment|time;
     repeated / type=un subject=id r;
     /* Could have used subject=monkey, but then monkey must be declared in
        class because it's character-valued. */

/* We did not reject the null hypothesis that observations from the
same subject are independent. Try an ordinary 2-way ANOVA, mostly 
for the interaction plot.  */

proc glm;
     title3 'Ordinary 2-way';
     class time treatment; /* This order determines the plot. */
     model score = treatment|time;

/* Could justify compound symmetry: Each monkey brings her own special talent
for discrimination learning.  */

proc mixed cl;
     title3 'Compound Symmetry';
     class treatment time;
     model score = treatment|time;
     repeated / type=cs subject=id r;

/* Contrast statements to follow up the interaction are possible 
   but challenging. */
   
data unimemory;
     infile '/folders/myfolders/monkey.data.txt' firstobs=2;
     input monkey $ treatment $ week2 week4 week8 week12 week16;
     twovs16 = week2-week16; /* Could do all 15 pairwise differences*/

proc glm;
     class treatment;
     model twovs16=treatment;

proc glm data=memory;
     title3 'Classical (Same results as CS)';
     class treatment time monkey;
     model score = treatment|time monkey(treatment);
     random monkey(treatment) / test;