Create summary for multiple iterations extracted from loop via single model

Question

I have created a function which is running multiple iteration of lm regression using different columns as the dependent variable over a loop. I am extracting the summary of each iteration and the relavance graph, but I am not able to create a single summary table of all the iteration results. Since I have only 8 columns, I think it can be done. Here's my function with data below

quantmodel<-function(a){
  i<-1
  a <- janitor::clean_names(a)
  colnames1 <- colnames(a)
  lm_model <- linear_reg() %>% 
    set_engine('lm') %>%
    set_mode('regression')
  
  out_lst <- vector('list', ncol(a))
  
  for (i in seq_along(a)) {
    lm_fit <- lm_model %>% 
      fit(as.formula(paste(colnames1[i], "~ .")), data = a)
    
    #Saving relevance plot of each parameter
    temp_plot = vip(lm_fit ,geom = "col", aesthetics = list(color = "black", fill = "black"))
    ggsave(temp_plot, file=paste0("plot_", i,".png"), width = 14, height = 10, units = "cm")
    #Saving pdf of individual summaries
    pdf(paste0("summary_", colnames1[i],".pdf"), width = 10,height = 3) 
    grid.table(coef(summary(lm_fit$fit)))
    dev.off()
    paste0("m",i)<-lm_fit$fit
  }
  
}

quantmodel(set1)

Data: Set1(first 3 columns)

Imp of family	Imp of friends	Imp of Leisure
2	1	1
1	2	1

Have a look at these previous questions: [R loop over linear regression](https://stackoverflow.com/questions/71546726/r-loop-over-linear-regression) and [R: How can I convert a list of linear regression results to a dataframe?](https://stackoverflow.com/q/71525639/17303805) — zephryl, Mar 27 '22 at 12:32

score 0 · Accepted Answer · answered Mar 27 '22 at 12:51

Since you do not provide a MINIMAL WORKING EXAMPLE, it is impossible for us to diagnose your problem correctly.

That said, one option would be to ensure that your function returns a list of models, and then feed that to the modelsummary function. In this example code, note the return() call at the end and the modelsummary() call:

quantmodel<-function(a){
  i<-1
  a <- janitor::clean_names(a)
  colnames1 <- colnames(a)
  lm_model <- linear_reg() %>% 
    set_engine('lm') %>%
    set_mode('regression')
  
  out_lst <- list()
  
  for (i in seq_along(a)) {
    lm_fit <- lm_model %>% 
      fit(as.formula(paste(colnames1[i], "~ .")), data = a)

    out_lst[[i]] <- lm_fit
    
    #Saving relevance plot of each parameter
    temp_plot = vip(lm_fit ,geom = "col", aesthetics = list(color = "black", fill = "black"))
    ggsave(temp_plot, file=paste0("plot_", i,".png"), width = 14, height = 10, units = "cm")
    #Saving pdf of individual summaries
    pdf(paste0("summary_", colnames1[i],".pdf"), width = 10,height = 3) 
    grid.table(coef(summary(lm_fit$fit)))
    dev.off()
    paste0("m",i)<-lm_fit$fit
  }

  return(out_lst)
  
}

library(modelsummary)
models <- quantmodel(set1)
modelsummary(dvnames(models))

Understood. Thanks for the example. Seems like with a few datatype changes, it would work. Thanks a lot. — Abhishek Pant, Mar 27 '22 at 13:48

Create summary for multiple iterations extracted from loop via single model

1 Answers1