Hello everyone, I’m working on a repeated measures analysis of nitrous oxide flux data collected over the  growing season, with measurements taken every two weeks from May to July. I’m trying to analyze this data using proc glimmix in SAS, but I’m unsure if my code is correct.  I’m confused about: Whether my proc glimmix setup is appropriate for repeated measures analysis. Whether checking normality on is the correct approach? Could someone help clarify the correct way to specify repeated measures in GLIMMIX and properly check normality for this type of data? Thank you!     Options nocenter pageno=1; *title 'GLIMMIX F19 ALPHA 0.05'; data F22; input blk treat HY$ nflux; cards; 1  1   may  data .( This is data section with block, treatment number sample time(may to july) as HY nitrous oxide flux as nflux) . . . . . . . . 4 2 june data run;   proc sort data= F22; by treat; proc means data=F22 n nmiss min mean max std stderr; var nflux;  by treat; run;   proc sort data= F22; by HY; proc means data=F22 n nmiss min mean max std stderr; var nflux;  by HY; run;     proc sort data= F22; by treat HY; proc means data=F22 n nmiss min mean max std stderr; var nflux;  by treat HY; run;   proc glimmix method=rmpl data=F22;  nloptions tech=newrap maxiter=1000; class blk treat HY; model nflux = treat HY treat*HY/ddfm=kenwardroger; random blk/ solutionr; random intercept/subject=blk;  ods output solutionr=Rdmdata; random HY/ residual subject=blk*treat type = arh(1);  lsmeans treat HY treat*HY/pdiff adjust=tukey lines alpha=0.05;  ods output tests3=tests diffs=ppp lsmeans=mmm lsmlines=lines; run;   proc univariate data=Rdmdata plot normal; var estimate; run;   ... View more