Hello,
Not possible with lmer? I think it is.
At least with the first example of ?lmer it is:
library(lme4)
Days <- sleepstudy$Days
data2 <- data.frame(X = Days, Y = Days, Z = Days)
nc <- ncol(data2)
lmer_list <- vector("list", length = nc)
for(i in seq.int(nc)){
#fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
fm1 <- lmer(sleepstudy[, 1] ~ data2[, i] + (data2[, i] | sleepstudy[,
3]))
lmer_list[[i]] <- fm1
}
Anyway, if your subsetting is based on an index, consider coercing the
data.frame to (numeric) matrix first, it will speed up things.
And use the standard way with a data argument for the other terms:
data2 <- as.matrix(data2)
lmer_list2 <- vector("list", length = nc)
for(i in seq.int(nc)){
#fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
fm1 <- lmer(Reaction ~ data2[, i] + (data2[, i] | Subject), data =
sleepstudy)
lmer_list2[[i]] <- fm1
}
lmer_list[[1]]
lmer_list2[[1]]
Hope this helps,
Rui Barradas
Às 08:33 de 25/02/20, Federico Calboli escreveu:
Hi all,
I am struggling with an issue related to lme() and lmer(). lm() can easily
take stuff on the fly from different objects and be happy:
lm(data1[,1] ~ data2[,1] + data3[,45] + data4[,39])
works — always. It also allows me to run nice loops:
for(i in 1:whatever){
lm(data1[,1] ~ data2[,i] + data3[,45] + data4[,39])
}
(for a useless but clear example where I loop the model over all columns of
data2). This property also allows me to totally ignore ’names’ for the data I
am using.
I am at loss why this is not possible with lme() or lmer(). I can go around
this issue by building data frames on the fly, but this is cumbresome, both as
code and very likely as performance, especially looping over lots of data
having to generate these dummy data frames.
If there is a trick I am missing I’d be grateful if anybody could set me
straight.
Best
F
--
Federico Calboli
LBEG - Laboratory of Biodiversity and Evolutionary Genomics
Charles Deberiotstraat 32 box 2439
3000 Leuven
+32 16 32 87 67
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