[R-sig-ME] Random intercept/slopes on two correlated outcomes

Ramon Diaz-Uriarte rdiaz02 at gmail.com
Mon Feb 6 10:39:36 CET 2017

Hi Theodore,

If you want a reference for an example with lmer, Faraway's book,
"Extending the Linear Model with R: Generalized Linear, Mixed Effects and
Nonparametric Regression Models, 2nd ed.", on section 11.3 contains an
example on using lmer with multiple responses. But this is basically the
answer that Thierry gave you (and Thierry's answer is adapted to your own



On Wed, 01-02-2017, at 15:44, Houslay, Tom <T.Houslay at exeter.ac.uk> wrote:
> Hi Theodore, just in case it's of interest, there is another option - ASReml (commercial software from VSNi) can fit the type of model you are looking for, with more complex variance structures (and it has an R interface). This thread from the forum might be informative in terms of how to set up such a model:
> http://www.vsni.co.uk/forum/viewtopic.php?t=1202
> Cheers (and good luck!)
> Tom
> ________________________________
> From: R-sig-mixed-models <r-sig-mixed-models-bounces at r-project.org> on behalf of r-sig-mixed-models-request at r-project.org <r-sig-mixed-models-request at r-project.org>
> Sent: 01 February 2017 09:40
> To: r-sig-mixed-models at r-project.org
> Subject: R-sig-mixed-models Digest, Vol 122, Issue 1
> Date: Wed, 01 Feb 2017 10:37:44 +0200
> From: Theodore Lytras <thlytras at gmail.com>
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Random intercept/slopes on two correlated outcomes
> Message-ID: <3197712.2r4pMF0lQW at equinox2>
> Content-Type: text/plain; charset="us-ascii"
> Hi all,
> I have repeated measures on individuals, and I'm fitting two LMMs with random
> intercepts and slopes per participant, on two outcomes (Y1, Y2) as follows:
> library(lme4)
> m1 <- lmer(Y1 ~ age + X + (age | id), data=dat)
> m2 <- lmer(Y2 ~ age + X + (age | id), data=dat)
> Fixed covariates for the two outcomes are the same, and id = participant ID.
> However, my two continuous outcomes Y1 and Y2 are correlated (highly), thus I
> would like to jointly model them (including estimating their correlation).
> What is the appropriate way to do so in this case? Can lme4 do it, or do I
> have to resort to MCMCglmm or JAGS? Could someone point me in the right
> direction (for either lme4, MCMCglmm or JAGS), including any helpful papers,
> guides, etc ??
> Thank you,
> Theodore Lytras
> Epidemiologist, PhD student
> Hellenic Centre for Disease Control and Prevention
> 	[[alternative HTML version deleted]]
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Ramon Diaz-Uriarte
Department of Biochemistry, Lab B-25
Facultad de Medicina
Universidad Autónoma de Madrid
Arzobispo Morcillo, 4
28029 Madrid

Phone: +34-91-497-2412

Email: rdiaz02 at gmail.com
       ramon.diaz at iib.uam.es


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