Hi,
I have a large matrix (SNPs) that I want to cycle over with logistic
regression with interaction terms. I have made a loop but I am struggling
to identify to the formula the name of the column in a way which is
meaningful to the formula. It errors becasue it is not evaluated proporly.
(below is a pilot with only 7 to 33 columns, my actual has 200,000 columns)
My attempts:
for (i in 7:33) {
label <- colnames(n)[i]
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
} #variable lengths differ
Error in model.frame.default(formula = AS ~ label, data = n,
drop.unused.levels = TRUE) :
variable lengths differ (found for 'label')
#This is because it is trying to do logistic regression on a character
string
for (i in 7:33) {
label <- eval(colnames(n)[i])
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
} #variable lengths differ
Error in model.frame.default(formula = AS ~ label, data = n,
drop.unused.levels = TRUE) :
variable lengths differ (found for 'label')
#same as above
for (i in 7:33) {
label <- as.name(colnames(n)[i])
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
}
Error in model.frame.default(formula = AS ~ label, data = n,
drop.unused.levels = TRUE) :
invalid type (symbol) for variable 'label
#not sure what this error is
for (i in 7:33) {
label <- eval(as.name(colnames(n)[i]))
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
}
# Error in eval(expr, envir, enclos) : object 'B1' not found
B1 is the name of the first column - this isn't an object and that seems to
be why it is causing an error
for (i in 7:33) {
label <- as.formula(colnames(n)[i])
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
}
Error in eval(expr, envir, enclos) : object 'B1' not found
#same as above
for (i in 7:33) {
label <- eval(as.formula(colnames(n)[i]))
model1 <- glm(AS~label*interaction,family=binomial("logit"),data=n)
X <- summary(model1)$coefficients[2,1]
Y <- c(label,X)
vector <- rbind(vector,Y)
}
Error in eval(expr, envir, enclos) : object 'B1' not found
#same as above
Any help would be appreciated.
Thanks
Philip
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