R：使用 glm-function 应用列表

Question

I'm having trouble trying to put variables, which are in list, into a glm -function. My dataframe has lots of variables, so it would be too much effort to type the independent variables one by one into glm . Lets say my dataframe is

df <- data.frame(
  id = c(1,2,3,4,5),
  `sitting position` = c("A","B","A","A","B"),
  `variable one` = c("left", "left", "right", "right", "left"),
  `variable two` = c(50, 30, 45, 80, 57),
  `variable three` = c("m","w","w","m","m"),
  check.names = FALSE)

and my list of columns which I want to use in a glm -function looks like this

columns <- dput(colnames(df))[-c(1:2)]

columns 
[1] "variable one"   "variable two"   "variable three"

Now I want to put this list directly into a glm - function, something like

glm(`sitting position` ~ columns, data = df, familiy = binomial).

instead of

glm(`sitting position` ~ `variable one` + `variable two` + `variable three`, data = df, family = binomial())

I am aware that I can't work just by adding the list, but I also can't find a solution to fix this problem.

Answer 1

Maybe we can use reformulate . reformulate will create formulas from character vectors. We can feed the output of reformulate into the formula argument to the glm function.

I included a preliminary step to replace your column names with a cleaner and less buggy alternative with janitor::clean_names .

library(janitor)

df<-df %>% clean_names
columns<-c('variable_one', 'variable_two', 'variable_three')

And then the actual solution:

glm(formula=reformulate(termlabels = columns, response='sitting_position'), data=df)

See how reformulate works:

reformulate(termlabels = columns, response='sitting_position')

sitting_position ~ variable_one + variable_two + variable_three