thank you! ... View more

Thanks Ameriel this is very helpfull!   so i used this code to ask for residuals and store them in 'resburn':   proc mixed data= ewcsrotatie noclprint noitprint covtest; class countid; model burnout= ondergekwa overgekwa man leeftijd loon stopstudeer nonprofit privaat combo ondergekwa*stopstudeer overgekwa*stopstudeer /solution residual outpm=resburn; random intercept / solution sub=countid; run;   and now i wanted to do a 'proc univariate' where data= resburn but i don't know what should come after the var statement?  ... View more

Hi ameriel,   Thanks for helping!   Point A: shoudln't it be:  "for large sample sizes even small deviations from normality would lead to a NON significant normality test" ?   I added the outcome of the proc univariate in attachement( i also added a qqplot). My problem is that the histogram and qqplot looks normal (I think) but for my thesis i would be better to base this on a number because i'm not sure when i can say that a qqplot or histogram is no longer normal. with a number there is a clear line.    I also think it is weird that when i use any other variable (as a test) like 'how many hours do you work a week' that the p-values for these three test remain exactly the same.      ... View more

this is the code i use for variable burn-out:   proc univariate data= ewcsrotatie normal plot; var burnout ; histogram burnout / NORMAL (MU=EST SIGMA=EST); qqplot burnout / NORMAL (MU=EST SIGMA=EST); run;   There are no errors or warnings but even if i take a variable like 'how many hours do you work a week' i still get the exact same p-values so there's never a normal distributon.  (Maybe good to know my dataset had over 43000 cases)     thanks!   ... View more