This system of styles, templates, destinations is just about incomprehensible. ... View more

Thank you for the reply, but I am still too ignorant to make full use of it.  I don't know what I am looking at in the registry, so I'll avoid doing anything there.  What is ODS systole? It doesn't turn up on a Google search.   Finally, let's say I want the Journal style with Calibri font, is this the syntax for that?  proc template; define style styles.my_journal; parent=styles.journal; class GraphFonts /           "GraphAnnoFont" = ("<sans-serif>, Calibri", 10pt)           "GraphAnnoFont" = ("<sans-serif>, Calibri", 10pt) ...... etc   ... View more

I have been thru the documentation.  It may be a deficit in my knowledge, but seeing the definitions of the covariance estimators doesn't suggest much too me in terms of useful information.    I opted for one of the simpler ones, as the problem isn't big.  As for NLP v OPTMODEL, NLP is working and is so much less messy than OPTMODEL, that I'll stick with it for this project.    ... View more

This is an old thread.  Has any progress been made?  Is there a way, with SAS, to carry out quantile regression with longitudinal data?  The Effect option on proc quantreg was mentioned but that doesn't account for the serial dependence in the data. ... View more

If means are appropriate, try glmselect. If you want to model the median or other quantile, then quantreg. ... View more

What you do depends on what exactly is the research question.  Nonetheless, to make this a typical logistic regression problem you need a yes/no outcome. You could form that by having the clinicians select a meaningful threshold, like TV reduced by 10%, yes/no.  That makes for a logistic regression, but dichotomizing data often reduces power, and sort of muddies the interpretation.  In my example, a reduction of 9.9% is a 'no' while 10.00 is a 'yes', but is there a meaningful difference in these two volumes?   Relative % change = (TV1-TV3)/TV1 = 1-TV3/TV1.  Even if TV is normally distributed the ratio TV3/TV1 almost surely isn't normal.  From your data example it doesn't look like TV2 is used.   So you could use the Kruskal-Wallis test, available with the Wilcoxon option in proc npar1way, to compare groups and not have to be concerned with parametric assumptions.   If the overall test is significant, the DSCF for the pairwise comparisons.   There is a literature, mostly based on simulations, suggesting that ANCOVA with TV1 as the covariate is the preferred analysis.  Here is an easy read on the subject:  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC34605/       ... View more

Now that I know I feel like I should have seen that!  Thank you.   ... View more