MCMCglmm: correslation between variables two variables in repeated measure?
Jarrod Hadfield <j.hadfield at ...> writes:
Hi, Section 5.1 of the CourseNotes demonstrates how to fit such a model. A limitation of MCMCglmm if there are >2 time points is that there will probably be temporal auto-correlation which will not be accounted for by simply fitting subject as a random effect. ASReml would allow you to include temporal auto-correlation if needed, and possibly lme. Jarrod
I would say that lme would allow you to fit this model, something like: (1) "melt" your data (possibly using melt() from the reshape package so that it is structured as subject time var value 1 1 1 0.2342 1 1 2 0.2 1 2 1 0.3 1 2 2 0.1 ... etc. then you can model this in lme() via something like: lme(value~(var-1),random=~var|subject/time,correlation=corAR1(~time|subject)) (you should probably check for yourself that this makes sense ...) This only tests correlation within subjects -- I'm not sure how to think about correlation within time, across subjects ...
Quoting Ndjido Ardo BAR <ndjido at ...> on Sun, 3 Jul 2011 13:31:05 +0200:
Hi all, I'd like to test for correlation between two variables that represent repeated measures (over time) on subjects of a follow-up. Test for correlation is both within and accross subjects. The first idea that hits my mind is to use a bivariate model for exemple using MCMCglmm. I'd like to know if this idea can lead to something correct. cheers, Ardo.