@Ksharp  This particular programming issue is something we have to deal with all the time, so I just de-identified the code and added the messages.  Not a programmer except for very specific data manipulations to get stuff in shape for analysis   SteveDenham ... View more

The RANDOM statement specifies INTERCEPT with subject=family - so that estimates the variance component due to family.  By including VISNO in the statement, you also estimate a component for family*visno and the covariance between these. The REPEATED statement specifies the within subject variability over time by family {the subject=dbid(family) provides this}.   This is equivalent to a random intercept and random slope for subject and a random intercept for family.   If the time points are evenly spaced, I would be inclined to make one change - from type=cs to type=ar(1) in the REPEATED statement.  I find it difficult to imagine that the covariances between the residuals at all time points are equal.  Most temporal repeated measures have a greater covariance for time points that are closer together than those that are more separated in time.   SteveDenham ... View more

I like @Ksharp 's approach.  Here is yet another way using PROC MEANS.   data have; input Group $ ClassValue; datalines; a 1 b 2 a 2 c 2 d 3 b 2 ; proc means data=have noprint; class group; var classvalue; output out=want stddev=stddev; run; data want2; length msg $50; set want; if _type_=0 then delete; if stddev=0 then msg='No variability in group'; else if stddev=. then msg='Insufficient number of observations in group'; else msg='Variability exists in group'; run; proc print data=want2; var msg group; run; SteveDenham ... View more

There are a couple of things to consider here.  First, how many levels are included in the variable TIME?  The unstructured covariance matrix requires estimating N*(N+1)/2 parameters where N is the number of levels. Next, you should not have FAMILY as the subject in your RANDOM statement when it is included as a random effect.  These two things are almost certainly the cause of the long run-time.  Try the following:   PROC MIXED DATA = PHENOTYPE_PGS_STD; CLASS DBID FAMILY TIME GENDER; MODEL Z_STAY_RCL = PGS_APP_DOLD AGEATVISIT GENDER VISNO / CHISQ S DDFM = BW; RANDOM INTERCEPT FAMILY / TYPE = UN SUBJECT = DBID G; REPEATED TIME / TYPE = AR(1) SUBJECT = DBID R; RUN; I changed the REPEATED type to an autoregressive error, which is appropriate if the levels of TIME are equally spaced.  If they are not equally spaced, a spatial power structure or a spline structure may be more appropriate.  The latter is only available in GLIMMIX, and only as a G side structure.  But first try the code above and see what happens.   One other thing to think about.  By using VISNO in the model, you are assuming a linear relationship between time and the dependent variable.  Shifting to TIME in the model would allow for a more flexible relationship, at the cost of increased model complexity and run time.   SteveDenham   ... View more

I hope I am answering the right question. Variance of a beta variable at the mean can be calculated from the mean and scale as mean*(1-mean)/(1+scale). The residual is simply observed value minus predicted value.   I am more concerned that you get different results when specifying link=logit as compared to no link statement, as the canonical link for the beta is the logit.  They ought to be the same.  All I can suggest is something I learned here last week - the data must be the "same", and that includes the order of the observations. So check for any PROC SORT statements prior to your GLIMMIX.   SteveDenham ... View more

This looks to me to be a lot like what the %NLmeans macro is meant for.  Calling @StatDave  as he seems to be the guru in this area.   SteveDenham ... View more

Jill,   That sound you heard a minute ago was me slapping my forehead.  You kept saying that the data were different, and since there were no missing values, it had to be in the sort.  Once sorted with period as the first key, the two methods agree completely.  Thanks for taking all of the time to help out on this.   SteveDenham ... View more