Using lmer() on my data results in an error. The problem,
I think, is my model specification. However, lm() works
ok.
I recreated this error with a more simple dataset. (See
code below.)
# word and letter recognition data
# two within factors:
# word length: 4, 5, 6 letters
# letter position: 1-4 (in 4-letter words), 1-5 (in
5-letter words), 1-6 (in 6-letter words)
# one dependent variable:
# reaction time
# make artificial data
length <- c(rep(4,4), rep(5,5), rep(6,6)) # independent
variable "word length"
length <- factor(c(rep(length, 2)))
pos <- c(1:4, 1:5, 1:6) # independent variable "letter
position"
pos <- factor(c(rep(pos, 2)))
rt <- c(rnorm(15, 200, sd=10), rnorm(15, 300, sd=15)) #
dependent variable "reaction time"
df <- data.frame(subj=factor(c(rep(1:2, each=15))),
length=length, pos=pos, rt=rt)
# to use lmer from lme4 package
library(lme4)
# first fit a linear model with letter position nested in
word length
lm(rt ~ length + length:pos, data=df)
# fit a mixed effects model, with subj (participant) as
random effect
lmer(rt ~ length + length:pos + (1 | subj), data=df)
Using lmer() results in an error: Error in
mer_finalize(ans) : Downdated X'X is not positive
definite, 13. I don't experience any problems using lm().
Does anyone know where things go wrong?
~ Ben Meijering
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