[R] Possible bug in lmer nested analysis with factors

[Doran, Harold]

I think you might have confused lme code with lmer code. Why do you have
c/d in the random portion?

I think what you want is

> lmer(a ~ b + (1 | c)+(1|d))

Which gives the following using your data


Linear mixed-effects model fit by REML
Formula: a ~ b + (1 | c) + (1 | d) 
      AIC      BIC    logLik MLdeviance REMLdeviance
 108.0239 115.9415 -49.01193   94.57296     98.02386
Random effects:
 Groups   Name        Variance   Std.Dev.  
 d        (Intercept) 4.2877e-10 2.0707e-05
 c        (Intercept) 4.2877e-10 2.0707e-05
 Residual             8.5754e-01 9.2603e-01
# of obs: 36, groups: d, 3; c, 2

Fixed effects:
            Estimate Std. Error DF t value Pr(>|t|)  
(Intercept)  0.82928    0.40834 34  2.0309  0.05015 .
b           -0.37563    0.18903 34 -1.9872  0.05500 .
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Yan Wong
Sent: Friday, September 16, 2005 11:58 AM
To: R-help
Subject: [R] Possible bug in lmer nested analysis with factors

Hello,

Is this a bug in the lmer routine?

 > library(lme4)
 > ### test case based on rats data from Crawley  >
a<-rnorm(36);b<-rep(1:3,each=12);c<-rep(1:2,each=6,3);d<-rep
(1:3,each=2,6)
 >
 > ### mixed model works when c & d are numeric, lmer assumes they are
factors  > m <- lmer(a ~ b + (1|c/d))  >  > ### but bails out when they
are actually specified as factors  > c<-factor(c); d<-factor(d)  > m <-
lmer(a ~ b + (1| c / d))

Error in lmer(a ~ b + (1 | c/d)) : entry 0 in matrix[0,0] has row
2147483647 and column 2147483647
In addition: Warning message:
/ not meaningful for factors in: Ops.factor(c, d)


Cheers

Yan

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