[R-sig-ME] Error in lme4 0.999902344-0: "Object 'multResp' not found" ?

Douglas Bates bates at stat.wisc.edu
Thu May 24 20:17:16 CEST 2012


On Thu, May 24, 2012 at 10:30 AM, Bertolt Meyer <bmeyer at sozpsy.uzh.ch> wrote:
> Dear list,
>
> The simplest random intercept model that I try to fit with the newest version of lme4 (0.999902344-0) throws an "Object 'multResp' not found" error on my Mac (Mac OSX 10.7.3, German R 2.15.0). Here is a reproducible example:
>
> install.packages(c("minqa", "Rcpp"))
> install.packages("lme4", repos="http://lme4.r-forge.r-project.org/repos")
> library(lme4)
>
> my_data <- read.csv("http://dl.dropbox.com/u/5384027/my_data.csv")
> my_data$group <- as.factor(my_data$group)
>
> # the data set consists of 97 four-person teams
> # with two variables x and y observed on the individual
> # level in each team
>
> head(my_data)
> #   X group        y          x
> # 1 1     1 2.914286  -8.170984
> # 2 2     1 2.746269 -13.504318
> # 3 3     1 3.171429  -1.504318
> # 4 4     1 2.978723  -4.837651
> # 5 5     2 2.928571  -8.170984
> # 6 6     2 2.987013   8.495682
>
> mlmodel1_ri <- lmer(y ~ x + (1 | group), data = my_data)
>
> # Fehler in lmer(y ~ x + (1 | group), data = my_data) :
> #   Objekt 'multResp' nicht gefunden
>
> Does anyone know how to fix this?

Not a problem on an Ubuntu system.  It may be something to do with the
version of the Mac OS X package on R-forge.  Ben is the person who
creates those and he is very busy right now with teaching obligations.
 Do you have the capability of compiling the source package?

Here are the results on an Ubuntu 12.04 system

> library(lme4)
Loading required package: lattice
Loading required package: Matrix
> str(my_data <- within(read.csv("http://dl.dropbox.com/u/5384027/my_data.csv"),
+                       group <- factor(group)))
'data.frame':	386 obs. of  4 variables:
 $ X    : int  1 2 3 4 5 6 7 8 9 10 ...
 $ group: Factor w/ 97 levels "1","2","3","4",..: 1 1 1 1 2 2 2 2 3 3 ...
 $ y    : num  2.91 2.75 3.17 2.98 2.93 ...
 $ x    : num  -8.17 -13.5 -1.5 -4.84 -8.17 ...
> print(fm1 <- lmer(y ~ x + (1|group), my_data))
Linear mixed model fit by REML ['lmerMod']
Formula: y ~ x + (1 | group)
   Data: my_data

REML criterion at convergence: 142.4097

Random effects:
 Groups   Name        Variance Std.Dev.
 group    (Intercept) 0.02075  0.1440
 Residual             0.06639  0.2577
Number of obs: 386, groups: group, 97

Fixed effects:
            Estimate Std. Error t value
(Intercept) 2.877840   0.019648  146.47
x           0.001337   0.001264    1.06

Correlation of Fixed Effects:
  (Intr)
x 0.002



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