[R-sig-ME] contrast of predicted slopes from MCMCglmm model

[Daniel Fulop]

Hi Russ,

Thanks a ton!  I did notice that lsmeans could be extended, but wasn't 
sure of how to get all the pieces from my MCMCglmm model object.  I was 
going to start getting the slopes from predictions on a grid of 'day' 
values to then average and finally subtract averages to contrast, but 
you've spared me that trouble.  Plus, I already have code to summarize 
and plot growth rate results from lsmeans, which I can now reuse.

I have one question about your example code, though.  Since I have 
posterior estimates, wouldn't it be better to get the bhat vector by 
using posterior.mode() instead of mean()?

Thanks,
Dan.


Lenth, Russell V wrote:
> Daniel,
>
> As long as you can get the regression coefficients, covariance of the coefficients, and a suitable grid of linear functions, you can obtain an lsmobj object that can be summarized and further analyzed in the 'lsmeans' package. For your question, I think something like this will work (I'm assuming your fitted mcmcGLMM object is named 'mod'):
>
> # Get coefs and covariance matrix
> bhat<- apply(mod$Sol, 2, mean)
> V<- cov(mod$Sol)
>
> # Set up desired factor levels (you likely want to change this)
> levels<- list(day = 1:4, treatment = c("control", "cold"), species = factor(1:10))
>
> # Obtain a differece quotient of model matrices
> lv1<- lv2<- levels
> lv1$day = lv1$day - .0001
> lv2$day = lv2$day + .0001
> grid1<- do.call(expand.grid, lv1)
> grid2<- do.call(expand.grid, lv2)
> lf1<- model.matrix(fixedForm, data = grid1)
> lf2<- model.matrix(fixedForm, data = grid2)
> linfct<- (lf2 - lf1) / .0002
>
> # Create the needed lsmobj
> library(lsmeans)
> mod.lsm<- lsmobj(bhat = bhat, V = V, levels = levels,
>      linfct = linfct, by = "species")
>
> # Can now use summary, contrast, pairs, etc. on this result
>
>
> I hope this helps
>
> Russ
>
> Russell V. Lenth  -  Professor Emeritus
> Department of Statistics and Actuarial Science
> The University of Iowa  -  Iowa City, IA 52242  USA
> Voice (319)335-0712 (Dept. office)  -  FAX (319)335-3017
>
>
> -----Original Message-----
> Date: Thu, 09 Apr 2015 18:32:11 -0700
> From: Daniel Fulop<dfulop.ucd at gmail.com>
> To: R_MixedModels<r-sig-mixed-models at r-project.org>
> Subject: [R-sig-ME] contrast of predicted slopes from MCMCglmm model
> Message-ID:<5527281B.3080607 at gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Hi mixed modelers,
>
> I would like to contrast average slopes using predictions from an LMM model fit with MCMCglmm.  In essence I want to do something analogous to lsmeans' lstrends() function.  The predicted slopes are growth rates ...more below.
>
> I have 12 days of plant growth data for 10 closely related species at 2 temperatures.  There are several individuals per species at each temperature, and they're fully randomized.  I want to asses whether each species' growth rate differs between temperatures.  What I mean by that is that I would like to contrast the average slopes for each species in control vs. cold temperature; these slopes are the growth rates.
>
> I am modeling the data in MCMCglmm so I can account for phylogeny and also to be able to try multi-response models (to jointly model the stem, plastochrons, root, etc).  I am starting out with the stem length data and after trying different time dependencies settled on this 3rd degree polynomial model:
>
> stemLen ~ poly(day, 3, raw=TRUE) * treatment * species + (1 + day | indiv)
>
> where day is a numeric time variable, treatment a 2 level factor (control and cold), and species a 10 level factor.
>
> I have a slight idea of how I would go about contrasting the average slopes for each species and that I would use the predict.MCMCglmm() function, but I would really appreciate some guidance before I go down the wrong the wrong path.
>
> Thanks for your help!
> Dan.
>
> --
> Daniel Fulop, Ph.D.
> Postdoctoral Scholar
> Dept. Plant Biology, UC Davis
> Maloof Lab, Rm. 2220
> Life Sciences Addition, One Shields Ave.
> Davis, CA 95616
>

-- 
Daniel Fulop, Ph.D.
Postdoctoral Scholar
Dept. Plant Biology, UC Davis
Maloof Lab, Rm. 2220
Life Sciences Addition, One Shields Ave.
Davis, CA 95616

510-253-7462
dfulop at ucdavis.edu