how do i exclude specific variables from a glm in R?

Question

I have 50 variables. This is how I use them all in my glm.

var = glm(Stuff ~ ., data=mydata, family=binomial)

But I want to exclude 2 of them. So how do I exclude 2 in specific? I was hoping there would be something like this:

var = glm(Stuff ~ . # notthisstuff, data=mydata, family=binomial)

thoughts?

Solution

In addition to using the - like in the comments

glm(Stuff ~ . - var1 - var2, data= mydata, family=binomial)

you can also subset the data frame passed in

glm(Stuff ~ ., data=mydata[ , !(names(mydata) %in% c('var1','var2'))], family=binomial)

or

glm(Stuff ~ ., data=subset(mydata, select=c( -var1, -var2 ) ), family=binomial )

(be careful with that last one, the subset function sometimes does not work well inside of other functions)

You could also use the paste function to create a string representing the formula with the terms of interest (subsetting to the group of predictors that you want), then use as.formula to convert it to a formula.

Comments

[rawr]

glm(Stuff ~ . - var1 - var2)

[rawr]

also, update(var, . ~ . - var1 - var2) would work

[user3399551]

I can only use update after i've already built my model, right?

[G. Grothendieck]

also glm(Stuff ~ ., data = subset(mydata, select = - c(var1, var2)), family = binomial)`

[user3399551]

Thanks, G.G. Good thinking. Is there any more merit to any one of these methods? Or is this all just preference - use whatever you want?

[rawr]

@user3399551 yes, you can only update an existing object