[R-sig-ME] variance explained by fixed effects in MCMCglmm

rafter sass ferguson liberationecology at gmail.com
Thu Jul 16 01:05:18 CEST 2015

I've been searching for ways to calculate some R^2-like statistics for a
multi-level multi-response model fit with MCMCglmm (with 3 Gaussian

I can see from the Course Notes and elsewhere that it's very
straightforward to calculate the variance explained by the random effects,
but after much searching I haven't found a discussion for fixed effects. It
looks like one option would be refitting with all my fixed effects as
random - but I'm concerned that might be bonkers, or that there might be an
easier way.

For previous multilevel modeling with lmer, I've used the approach
following Nakagawa et al. 2013 (A general and simple method for obtaining
R2 from generalized linear mixed-effects models. Methods in Ecology and
Evolution, 4(2), 133–142. http://doi.org/10.1111/j.2041-210x.2012.00261.x)
to calculate conditional and marginal R^2...
but I'm not sure how to adapt it for the (for me) brave new world of

I would be grateful for any advice!

Thanks so much for your time.


Rafter Sass Ferguson, MS
PhD Candidate | Crop Sciences Department
University of Illinois in Urbana-Champaign
518 567 7407

	[[alternative HTML version deleted]]

More information about the R-sig-mixed-models mailing list