Writing a loop in R for regression replacing independent variable for robustness check-CodePudding

I want to run a simple logit regression in R, where my dependent variable is whether a firm charges a positive price or not, and the key independent variable is number of competitors within an x mile radius of the firm. To operationalize the competition variable, I am looking at 1, 5, 10 and 50 miles radius.

I am not sure how to write the loop though, and the Error in eval(predvars, data, env) : object 'radius_i' not found when I run the loop below.

circle_radius = list("1", "5", "10", "15", "50")

for (i in seq_along(circle_radius)){
    my_logit_4_r[i]  <-  glm(price_b1 ~   radius_i , 
                            data=data1,
                            family = binomial(link='logit'))
    summary(my_logit_4_r[i])
   }

So I am not sure how to specify the loop, as I do not want to use brute force and write the 4 regressions separately. Would appreciate help on what error I am making.

CodePudding user response：

You have to change your code a bit - first, use get() to use the what you are trying to call from radius_[i] to be a covariate in your model - though this needs to be changed to get(paste0("radius_",i)) (assuming you have a covariate named radius_1, radius_5, and so on in your data1 data frame. Also, you might want to remove the seq_along(circle_radius) and just do circle_radius since seq_along will define i as 1, 2, 3, 4 and removing it will define it as "1", "5", "10", and "50". You also need to define my_logit_4_r as a list and use double bracket [[i]] when assigning to the list in the loop.

Below I have made the changes to make this clearer.

Since you didnt provide sample data, I am assuming your data look like this:

circle_radius <- list("1", "5", "10", "50")
data1 <- data.frame(price_b1 = runif(100),
                    radius_1 = runif(100),
                    radius_5 = runif(100),
                    radius_10 = runif(100),
                    radius_50 = runif(100))

Try the following code:

my_logit_4_r <- vector(mode = "list", length = length(circle_radius))
for (i in circle_radius){
  my_logit_4_r[[i]]  <-  glm(price_b1 ~  get(paste0("radius_",i)) , 
                         data=data1,
                         family = binomial(link='logit'))
  
  summary(my_logit_4_r[[i]])
}

The models wont converge with my sample data, but they attempt to run. If this doesn't work, please provide sample data and I update my answer.