Bivariate MCMCglmm with repeated measures

Hi Sam,

One option would be

random = ~us(stage):Individual, rcov=~units

where the random term is a 2x2 covariance matrix (between individual  
variances for each stage and the covariance between them). There is  
only a single residual variance in my model - but this is OK, with  
binary data it can't be estimated so there is no point trying to  
estimates separate residual variances for each stage. You will need to  
fix the residual variance at something though (I use 1).

If you only have Individual level covariates (i.e. no  
observation-level covariates) then you could group your binary  
responses into a binomial response and fit the model

random=NULL, rcov = ~us(stage):units

This will give (nearly) the same answers as the first model if you  
rescale the (co)variances as described in the CourseNotes.  It will be  
much faster too.

You might also want to consider models that deal with temporal  
autocorrelation, but these are not implemented in MCMCglmm.

Cheers,

Jarrod
Quoting "PATRICK, Samantha" <spatrick at glos.ac.uk> on Mon, 11 Aug 2014  
17:34:05 +0000:

Bivariate MCMCglmm with repeated measures

Thread (4 messages)