* day_day.sas;
options pageno=1 linesize=80;
goptions reset=all;
title "Two-way ANOVA for day";
title2 "Data from day and Reynolds (2007)";
data day;
input location $ exp $ day;
* Apply transformations here;
y = log10(day);
datalines;
Cool EC 22
Cool EC 20
Cool EC 19
Cool EC 19
Cool AC 65
Cool AC 51
Cool AC 70
Cool AC 78
FB EC 9
FB EC 10
FB EC 10
FB EC 10
FB AC 11
FB AC 10
FB AC 10
FB AC 11
RES EC 15
RES EC 12
RES EC 15
RES EC 11
RES AC 13
RES AC 14
RES AC 14
RES AC 13
;
run;
* Print data set;
proc print data=day;
run;
* Plot means, standard errors, and observations;
proc gplot data=day;
plot y*location = exp / vaxis=axis1 haxis=axis1 legend=legend1;
symbol1 i=std1mjt v=star height=2 width=3;
axis1 label=(height=2) value=(height=2) width=3 major=(width=2) minor=none;
legend1 label=(height=2) value=(height=2);
run;
* Two-way ANOVA with all fixed effects;
proc glm data=day;
class location exp ;
model y = location exp location *exp ;
lsmeans location exp / adjust=tukey cl lines;
output out=resids p=pred r=resid;
run;
* Two-way ANOVA with interaction;
title3 "MODEL WITH INTERACTION - USE THIS OUTPUT IF INTERACTION SIGNIFICANT";
proc glm data=day;
class location exp;
model y = location exp location*exp / ss2;
lsmeans location*exp / slice=exp exp=location;
output out=resids p=pred r=resid;
run;
goptions reset=all;
title "Diagnostic plots to check anova assumptions";
* Plot residuals vs. predicted values;
proc gplot data=resids;
plot resid*pred=1 / vaxis=axis1 haxis=axis1;
symbol1 v=star height=2 width=3;
axis1 label=(height=2) value=(height=2) width=3 major=(width=2) minor=none;run;
* Normal quantile plot of residuals;
proc univariate noprint data=resids;
qqplot resid / normal waxis=3 height=4;
run;
quit; Greeting All I run one way-ANOVA and I got the results as showed in the pictures attached, can get a similar result in Two-way ANOVA. Thanks in advance
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