loop through column glmer - r

Question

I am trying to run a glmer by looping through columns in my dataset which contain response variables (dat_prob).The code I am using is as follows, adapted from code researched on another stackoverflow question (Looping through columns in R).
Their code:
dat_y<-(dat[,c(2:1130)])
dat_x<-(dat[,c(1)])
models <- list()
#
for(i in names(dat_y)){
y <- dat_y[i]
model[[i]] = lm( y~dat_x )
}
My code:
dat_prob<-(probs[,c(108:188)])
dat_age<-(probs[,c(12)])
dat_dist<-(probs[,c(20)])
fyearcap=(probs[,c(25)])
fstation=(probs[,c(22)])
fnetnum=(probs[,c(23)])
fdepth=(probs[,c(24)])
models <- list()
#
for(i in names(dat_prob)){
y <- dat_prob[i]
y2=as.vector(y)
model[[i]] = glmer( y ~ dat_age * dat_dist + (1|fyearcap) + (1|fstation)+
(1|fnetnum)+ (1|fdepth),family=binomial,REML=TRUE )
}
And I receive this error, similar to the error received in the hyperlinked question:
Error in model.frame.default(drop.unused.levels = TRUE, formula = y ~ :
invalid type (list) for variable 'y'
I have been working through this for hours and now can't see the forest through the trees.
Any help is appreciated.

Answer 1

y <- dat_prob[i] makes y a list (or data frame, whatever). Lists are vectors - try is.vector(list()), so even y2 = as.vector(y) is still a list/data frame (even though you don't use it).
class(as.vector(mtcars[1]))
# [1] "data.frame"
To extract a numeric vector from a data frame, use [[: y <- dat_prob[[i]].
class(mtcars[[1]])
# [1] "numeric"
Though I agree with Roman - using formulas is probably a nicer way to go. Try something like this:
for(i in names(dat_prob)) {
my_formula = as.formula(paste(i,
"~ dat_age * dat_dist + (1|fyearcap) + (1|fstation)+ (1|fnetnum)+ (1|fdepth)"
))
model[[i]] = glmer(my_formula, family = binomial, REML = TRUE)
}
I'm also pretty skeptical of whatever you're doing trying 80 different response variables, but that's not your question...