CODEWITHSUNDEEP
rloopslm
queserasera
queserasera

Reputation: 71

How do I select two factors and perform regression

I have a dataset like this:

library(tidyverse)
set.seed(123)
Data <- data.frame(
        X = sample(c("A", "B", "C"), 20, replace = TRUE),
    Y = sample(1:20)
)
Data%>%
    arrange(X)

I would like to run series of regressions such that DV is Y but independent variables for each regression are factors taken two at a time. For instance, A&B, A&C,B&A,B&C Thanks for your help.

Upvotes: 0

Views: 134

Answers (1)

Obim
Obim

Reputation: 136

For linear regression:

> combos <- as.data.frame(x = combn(x = c("A", "B", "C"), m = 2))
names(combos) <- sapply(
  X = 1:3, 
  FUN = function(x){paste(combos[,x], collapse = "")}
)

> fit.list <- list()
> for (combo in names(combos)){
  fit.list[[combo]] <- subset(Data, X %in% combos[,combo]) %>% 
    lm(formula = .$Y ~ .$X, data = .)
}

> fit.list
$AB

Call:
lm(formula = .$Y ~ .$X, data = .)

Coefficients:
(Intercept)         .$XB  
       10.4          3.6  


$AC

Call:
lm(formula = .$Y ~ .$X, data = .)

Coefficients:
(Intercept)         .$XC  
       10.4         -2.9  


$BC

Call:
lm(formula = .$Y ~ .$X, data = .)

Coefficients:
(Intercept)         .$XC  
       14.0         -6.5

EDIT For adding a covariate (e.g. Z), one way is to add as a new column in the data.frame, then add the column name to the model:

> set.seed(123)
> Data <- data.frame(
  X = sample(c("A", "B", "C"), 20, replace = TRUE),
  Y = sample(1:20),
  Z = sample(1:20)
)

> fit.list <- list()
> for (combo in names(combos)){
  fit.list[[combo]] <- subset(Data, X %in% combos[,combo]) %>% 
    lm(formula = .$Y ~ .$X + .$Z, data = .)
}
> fit.list
$AB

Call:
lm(formula = .$Y ~ .$X + .$Z, data = .)

Coefficients:
(Intercept)         .$XB          .$Z  
     3.6697       3.1921       0.5099  


$AC

Call:
lm(formula = .$Y ~ .$X + .$Z, data = .)

Coefficients:
(Intercept)         .$XC          .$Z  
     7.9306      -1.5063       0.1871  


$BC

Call:
lm(formula = .$Y ~ .$X + .$Z, data = .)

Coefficients:
(Intercept)         .$XC          .$Z  
   14.89888     -7.02970     -0.06421

Upvotes: 2

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