Hi All,
I am currently conducting a mixed model. I have 7 repeated measures on a
simulated clinical trial. If I understand the model correctly, the
outcome is the measure (as a factor) the predictors are clinical group
and trial (1-7). The fixed factors are the measure and group. The random
factors are the intercept and id and group.
I tried using 2 functions to calculate mixed effects.
Following previous correspondence .
Dataset <- read.table("C:/Program Files/R/rw2011/data/miss/model1a.dat",
header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE)
attach(Dataset)
require (nlme)
with(Dataset, table(runnb, id, grp))
b.lvls <- table(Dataset$runnb)
nb <- length(b.lvls)
fit <- vector(mode="list", nb)
for(i in 1:nb)
fit[[i]]<- lme (trans1 ~ Index1 + grp,
random = ~ 1 | id / grp ,
data = Dataset,
na.action = "na.exclude")
This (above) worked OK only I am having memory problems.
I have a gig of RAM set at --sdi --max-mem-size=512M (complete version
below)
I am wondering if running the file as a database be slower / faster?
Then I read that lme4 does it quicker and more accurately
so I thought that I should re-run the code but from the for line:
> for (i in 1:nb)
+ fit[[i]] <- lmer(trans1 ~ Index1 + grp + (1|id:grp) + (1|id),
+ Dataset, na.action = na.exclude)
Producing
Error in lmer(trans1 ~ Index1 + grp + (1 | id:grp) + (1 | id), Dataset,
:
flist[[2]] must be a factor of length 200000
In addition: Warning messages:
1: numerical expression has 200000 elements: only the first used in:
id:grp
2: numerical expression has 200000 elements: only the first used in:
id:grp
Any advice on the source and handling of this error would be
appreciated?
version: _
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 1.1
year 2005
month 06
day 20
language R
Windows XP Pro.
Many thanks
Stephen
???? ?"? ???? ????
http://mail.nana.co.il
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