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glmmultivariate-testing
Judit M.
Judit M.

Reputation: 23

What statistic method to use in multivariate abundance data with random effects?

I am working with multivariate data with random effects.
My hypothesis is this: D has an effect on A1 and A2, where A1 and A2 are binary data, and D is a continuous variable.
I also have a random effect, R, that is a factor variable.

So my model would be something like this: A1andA2~D, random=1=~1|R

I tried to use the function manyglm in mvabund package, but it can not deal with random effects. Or I can use lme4, but it can not deal with multivariate data.

I can convert my multivariate data to a 4 level factor variable, but I didn't find any method to use not binary but factor data as a response variable. I also can convert the continuous D into factor variable.

Do you have any advice about what to use in that situation?

Upvotes: 1

Views: 705

Answers (1)

JonJup
JonJup

Reputation: 44

First, I know this should be a comment and not a complete answer but I can't comment yet and thought you might still appreciate the pointer.

You should be able to analyze your data with the MCMCglmm R package. (see here for an Intro), as it can handle mixed models with multivariate response data.

Upvotes: 1

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