Example 4 for PROC GLM
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: GLMEX4 */
/* TITLE: Example 4 for PROC GLM */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: Analysis of covariance */
/* PROCS: GLM */
/* DATA: */
/* */
/* SUPPORT: sasrdt */
/* REF: PROC GLM, EXAMPLE 4. */
/* Snedecor and Cochran (1967), Stat. Methods, p. 422. */
/* MISC: */
/****************************************************************/
/* Analysis of Covariance --------------------------------------*/
data DrugTest;
input Drug $ PreTreatment PostTreatment @@;
datalines;
A 11 6 A 8 0 A 5 2 A 14 8 A 19 11
A 6 4 A 10 13 A 6 1 A 11 8 A 3 0
D 6 0 D 6 2 D 7 3 D 8 1 D 18 18
D 8 4 D 19 14 D 8 9 D 5 1 D 15 9
F 16 13 F 13 10 F 11 18 F 9 5 F 21 23
F 16 12 F 12 5 F 12 16 F 7 1 F 12 20
;
proc glm data=DrugTest;
class Drug;
model PostTreatment = Drug PreTreatment / solution;
lsmeans Drug / stderr pdiff cov out=adjmeans;
run;
proc print data=adjmeans;
run;
/* Visualize the Fitted Analysis of Covariance Model -----------*/
ods graphics on;
proc glm data=DrugTest plot=meanplot(cl);
class Drug;
model PostTreatment = Drug PreTreatment;
lsmeans Drug / pdiff;
run;
ods graphics off;