Performing lm() and segmented() on multiple columns in R

Question

I am trying to perform lm() and segmented() in R using the same independent variable (x) and multiple dependent response variables (Curve1, Curve2, etc.) one by one. I wish to e

Answer 1

You can wrap the whole thing in a function, taking as the arguments the column name and the data, and use lapply on the column names, like this:

library(segmented)
run_mod <- function(varname, data){

  data$Y <- data[,varname]
  model <- lm(Y ~ x, data) # Linear model
  seg_model <- segmented(model, seg.Z = ~x) # Segmented model
  breakpoint <- as.matrix(seg_model$psi.history[[5]]) # Extract breakpoint
  coefficients <- as.matrix(seg_model$coefficients) # Extract coefficients
  summary_curve1 <- as.data.frame(rbind(breakpoint, coefficients)) 
  colnames(summary_curve1) <- varname

return(summary_curve1)
}


lapply(names(dat)[2:ncol(dat)], function(x)run_mod(x, dat))

Which gives the summary for each fitted curve (not sure which output you actually want).