[R-sig-ME] glmer model with independent random effects
Steve Walker
steve.walker at utoronto.ca
Wed Jun 4 14:09:19 CEST 2014
Odd. I get no problems on the current version of lme4 on CRAN. Can you
reproduce your problem with the example below? If so, is it possible to
update?
Steve
library(lme4)
set.seed(1)
m <- 50
n <- m^2
form <- y~ x1 + x2+(1|studyid) + ( x1 -1|studyid)+( x2 -1|studyid)
dat <- data.frame(studyid = gl(m, m),
x1 = rbinom(n, 1, 0.5), x2 = rbinom(n, 1, 0.5),
y = rep(0:1, length = n))
pars <- list(beta = setNames(1:3, c("(Intercept)", "x1", "x2")),
theta = setNames(rep(1, 3), c("studyid.(Intercept)",
"studyid.x1", "studyid.x2")))
dat$y <- unlist(simulate(form, newdata = dat, newparams = pars, family =
binomial))
glmer(form, dat, binomial)
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula: y ~ x1 + x2 + (1 | studyid) + (x1 - 1 | studyid) + (x2 - 1 |
studyid)
Data: dat
AIC BIC logLik deviance df.resid
1499.5705 1534.5148 -743.7852 1487.5705 2494
Random effects:
Groups Name Std.Dev.
studyid (Intercept) 0.8685
studyid.1 x1 0.7900
studyid.2 x2 0.6559
Number of obs: 2500, groups: studyid, 50
Fixed Effects:
(Intercept) x1 x2
0.6693 1.8733 2.8996
sessionInfo()
R Under development (unstable) (2014-03-08 r65144)
Platform: x86_64-apple-darwin10.8.0 (64-bit)
locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] lme4_1.1-6 Rcpp_0.11.1 Matrix_1.1-3 mysys_1.0
loaded via a namespace (and not attached):
[1] compiler_3.1.0 grid_3.1.0 lattice_0.20-27
[4] MASS_7.3-29 minqa_1.2.2 nlme_3.1-113
[7] RcppEigen_0.3.2.1.2 splines_3.1.0 tools_3.1.0
On 2014-06-04, 7:34 AM, Thomas Debray wrote:
> Dear userlist,
>
> I recently updated the lme4 package to version 1.0-6 and have the
> impression formulas are not interpreted exactly the same way as before.
>
> I am trying to fit a mixed effect model with independent random effects for
> the covariates, that is:
>
> logit(y_ij) = b_0i + b_1i x1_ij + b_2i x2_ij
> where
> b_0i ~ N(beta0, tau0)
> b_1i ~ N(beta1, tau1)
> b_2i ~N(beta2, tau2)
>
> i indicates the subject, j indicates an index of different study IDs.
>
> In want to specify random slopes for b1 and b2, and a random intercept for
> b0. The variables x0 and x1 are binary, and take values 0 or 1. I have
> constructed the following formula:
>
> "y~ x1 + x2+(1|studyid) + ( x1 -1|studyid)+( x2 -1|studyid)"
>
>
> In one of the earlier versions of lme4, I would have gotten something like this:
>
>
> Random effects:
> Groups Name Std.Dev.
> studyid (Intercept) 2.217e-04
> studyid.1 x1 2.518e-05
> studyid.2 x2 8.891e-05
>
>
> where tau0, tau1 and tau2 are indicated by the Std.Dev. Now, in the latest
> version of lme4 I get:
>
>
> Random effects:
> Groups Name Std.Dev. Corr
> studyid (Intercept) 2.217e-04
> studyid.1 x10 2.518e-05
> x11 4.480e-04 0.08
> studyid.2 x20 8.891e-05
>
> x21 1.108e-04 0.79
>
>
>
> Can someone tell me whether I am doing something wrong, or how I
> should adjust my formula to estimate the specified model?
>
>
> Thanks in advance!
>
>
> Thomas
>
> [[alternative HTML version deleted]]
>
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