R: Multiple Linear Regression with a specific rang

问题:

This question already has an answer here:

• short formula call for many variables when building a model [duplicate] 2 answers

It appears simple, but I don't know how to code it in R. I have a dataframe (df) with ~100 variables, and I would like to do a multiple regression between the response which is my First variable (Y) and the variables 25 to 60 as regressors. The problem is that I don't want to write each variable name like:

lm(Y~var25+var26+.......var60, data=df)

I would like to use something like [, 25:60] to select a complete range. I have tried it but doesn't works:

test <- lm(Y~df[, 25:60], data=df)
summary(test)

some idea?

回答1:

You could subset the dataset by selecting only those columns, and then do the lm.

lm(Y~., data=df1[c(1,25:60)])

Suppose, if you need var25 to var60 and if the data is ordered by column names

lm(Y~., data=df1[c(1,26:61)])   

Or another option would be to use paste to create the formula

lm(paste("Y ~", paste(paste0('var', 25:60), collapse="+")), data=df1)

data

set.seed(24)
df1 <- as.data.frame(matrix(sample(1:80, 20*101, replace=TRUE),
   ncol=101, dimnames=list(NULL, c('Y', paste0('var', 1:100)))))