## ANOVA for Latin Square Treatment Design

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/*          S A S   S A M P L E   L I B R A R Y                 */
/*                                                              */
/*    NAME: AOVLSQ                                              */
/*   TITLE: ANOVA for Latin Square Treatment Design             */
/* PRODUCT: STAT                                                */
/*  SYSTEM: ALL                                                 */
/*    KEYS: analysis of variance,                               */
/*   PROCS: ANOVA GLM MEANS                                     */
/*    DATA:                                                     */
/*                                                              */
/* SUPPORT:                             UPDATE:                 */
/*     REF:                                                     */
/*    MISC:                                                     */
/*                                                              */
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*------Change in Blood Sugar Levels in Mice: Latin Square-------*
|     Four groups of mice, four days, and four treatments are   |
| arranged in a latin square design. The response is the mean   |
| change in blood sugar for 6 animals. The treatments are levels|
| of insulin coded as follows:                                  |
|            Level  A for 150 micro units                       |
|                   B     300                                   |
|                   C     600                                   |
|                   D    1200                                   |
*---------------------------------------------------------------*;

data sugar;
input dAy Group \$ Insulin \$ Response;
datalines;
1 I   B -4.5
1 II  D 92.33
1 III C 59.83
1 IV  A -45.
2 I   C 91.83
2 II  A -48.33
2 III D 168.99
2 IV  B 89.
3 I   D 86.16
3 II  B -78.16
3 III A -24.17
3 IV  C 101.0
4 I   A -.17
4 II  C 68.83
4 III B 25.17
4 IV  D 177.17
;

proc print;
run;

proc anova;
classes day group insulin;
model response= day group insulin;
means day group insulin;
run; quit;

data sugar2;
set sugar;
if insulin='A' then ins=150;
else if insulin='B' then ins=300;
else if insulin='C' then ins=600;
else if insulin='D' then ins=1200;
run;

proc glm;
classes day group;
model response= day group ins ins*ins ins*ins*ins;
run; quit;

proc sort out=c;
by ins;
run;

proc means;
by ins;
var response;
run;

```