Looping through covariates in regression using R

I'm trying to run 96 regressions and save the results as 96 different objects. To complicate things, I want the subscript on one of the covariates in the model to also change 96 times. I've almost solved the problem but I've unfortunately hit a wall. The code so far is,

for(i in 1:96){

  assign(paste("z.out", i,sep=""), lm(rMonExp_EGM~ TE_i + Month2+Month3+Month4+Month5+Month6+Month7+Month8+Month9+
  Month10+Month11+Month12+Yrs_minus_2004 + 
  as.factor(LGA),data=Pokies))

}

This works on the object creation side (e.g. I have z.out1 - z.out96) but I can't seem to get the subscript on the covariate to change as well.

I have 96 variables called TE_1, TE_2 ... TE_96 in the dataset. As such, the subscript on TE_, the "i" needs to change to correspond to each of the objects I create. That is, z.out1 should hold the results from this model:

z.out1 <- lm(rMonExp_EGM~ TE_1 + Month2+Month3+Month4+Month5+Month6+Month7+Month8+Month9+
  Month10+Month11+Month12+Yrs_minus_2004 + as.factor(LGA),data=Pokies)

And z.out96 should be:

z.out96 <- lm(rMonExp_EGM~ TE_96+ Month2+Month3+Month4+Month5+Month6+Month7+Month8+Month9+
  Month10+Month11+Month12+Yrs_minus_2004 + as.factor(LGA),data=Pokies)

Hopefully this makes sense. I'm grateful for any tips/advice.

I would put the results in a list and avoid the for loop and assign statements

You can use a combination of reformulate and update to create your formula

orig_formula <- MonExp_EGM~ Month2+Month3+Month4+Month5+Month6+Month7+Month8+Month9+
 Month10+Month11+Month12+Yrs_minus_2004 + as.factor(LGA)


te_variables <- paste0('TE_', 1:96) 
# Or if you don't have a current version of R
# te_variables <- paste('TE', 1:96, sep = '_')  

 new_formula <- lapply(te_variables, function(x,orig = orig_formula) { 
    new <- reformulate(c(x,'.'))
    update(orig, new)})
 ## it works!    
new_formula[[1]]
## MonExp_EGM ~ TE_1 + Month2 + Month3 + Month4 + Month5 + Month6 + 
##   Month7 + Month8 + Month9 + Month10 + Month11 + Month12 + 
##   Yrs_minus_2004 + as.factor(LGA)
new_formula[[2]]
## MonExp_EGM ~ TE_2 + Month2 + Month3 + Month4 + Month5 + Month6 + 
## Month7 + Month8 + Month9 + Month10 + Month11 + Month12 + 
## Yrs_minus_2004 + as.factor(LGA)


models <- lapply(new_formula, lm, data = pokies)

There should now be 96 elements in the list models

You can name them to reflect your originally planned nnames

names(models) <- paste0('z.out', 1:96)
# or if you don't have a current version of R
# names(models) <-paste('z.out', 1:96 ,sep = '' )

and then access a single model by

 models$z.out5

etc

or create summaries of all of the models

 summaries <- lapply(models, summary)

etc....

 # just the coefficients
 coefficients <- lapply(models, coef)

 # the table with coefficient estimates and standard.errors

 coef_tables <- apply(summaries, '[[', 'coefficients')

来源：https://stackoverflow.com/questions/13302323/looping-through-covariates-in-regression-using-r

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loops

for-loop

regression