Thank you for your input.
Indeed I post and old code, my mistake.
My experiment was done for 5 years at the same location. But not in the same area or plants.
It was a randomized Split-plot design with the main plot =time and the sub-plot= cv and for each year it was measured the variable PE in each plot.
This is the code that I am using per year.
proc mixed data=xx order=data plots=all;
class rep cv time;
model pe=time cv time*cv/ddfm=satterth outp=ORP_data1 residual;
random rep time*rep/solution;
lsmeans cv time time*cv/ adjust=tukey;
run;
proc plot data=ORP_data1;
plot resid*pred;
run;
proc univariate data=ORP_data1 normal plot;
var resid;
run;
not sure the code to determine the homogeneity of variances without using Levene test with GLM.
proc glm data=xx;
class time;
model pe=time/ss3;
means time /hovtest=levene (type=abs);
run;
proc glm data=xx;
class cv;
model pe=cv/ss3;
means cv /hovtest=levene (type=abs);
run;
Also, after the single analysis per year. what I need to know is if the values of PE (variable measure each year) can be combined over the years using either proc mixed or proc glimmix
I was using this code but not sure if it's right
proc mixed data=xx covtest plots=all;
class rep loc cv time;
model pe= time | cv/dfm=satterth outp=file2 residual;
random loc rep(loc) cv(loc) time(loc)/solution;
lsmeans cv time cv*time/diff;
run;
I will really appreciate your help with these codes I am overwhelmed with the ammount of information thank you!
