Loop for glm model with changing number of variables

Question

I have a dataset with 1-3 versions of the dependent variable, and 10-15 independent variables. I\'d like to run a glm command for the model, but would like it to loop for ALL po

Answer 1

Maybe something like that:

dep_vars <- c("DepVar1", "DepVar2") 
ind_vars <- c("IndVar1", "IndVar2", "IndVar3")

# create all combinations of ind_vars
ind_vars_comb <- 
  unlist( sapply( seq_len(length(ind_vars)), 
          function(i) {
               apply( combn(ind_vars,i), 2, function(x) paste(x, collapse = "+"))
          }))

# pair with dep_vars:
var_comb <- expand.grid(dep_vars, ind_vars_comb ) 

# formulas for all combinations
formula_vec <- sprintf("%s ~ %s", var_comb$Var1, var_comb$Var2)

# create models
glm_res <- lapply( formula_vec, function(f)   {
    fit1 <- glm( f, data = dfPRAC, family = binomial("logit"))
    fit1$coefficients <- coef( summary(fit1))
    return(fit1)
})
names(glm_res) <- formula_vec

# get model for specific formula
glm_res[["DepVar1 ~ IndVar1"]] 

# coefficients for var1 ~ var1
coef(glm_res[["DepVar1 ~ IndVar1"]])

# p-values for var1 ~ var2
coef(glm_res[["DepVar1 ~ IndVar2"]])[,"Pr(>|z|)"]

# p-values in a data.frame
p_values <- 
  cbind(formula_vec, as.data.frame ( do.call(rbind,
        lapply(glm_res, function(x) {
          coefs <- coef(x)
          rbind(c(coefs[,4] , rep(NA, length(ind_vars) - length(coefs[,4]) + 1)))
        })
  )))

Result:

                         formula_vec (Intercept)    IndVar1         V3        V4
1                  DepVar1 ~ IndVar1  1.00000000 1.00000000         NA        NA
2                  DepVar2 ~ IndVar1  0.65526203 0.29437334         NA        NA
3                  DepVar1 ~ IndVar2  0.29307777 0.19121066         NA        NA
4                  DepVar2 ~ IndVar2  0.07298241 0.03858791         NA        NA
5                  DepVar1 ~ IndVar3  0.99950535 0.99940963         NA        NA
6                  DepVar2 ~ IndVar3  0.52105212 0.44715614         NA        NA
7          DepVar1 ~ IndVar1+IndVar2  0.31112860 0.76310468 0.18416266        NA
8          DepVar2 ~ IndVar1+IndVar2  0.06488501 0.08833369 0.03031766        NA
9          DepVar1 ~ IndVar1+IndVar3  0.99952006 0.99999188 0.99940957        NA
10         DepVar2 ~ IndVar1+IndVar3  0.38508258 0.29593637 0.45010697        NA
11         DepVar1 ~ IndVar2+IndVar3  0.28167430 0.15753070 0.54363164        NA
12         DepVar2 ~ IndVar2+IndVar3  0.22644873 0.04654188 0.84059019        NA
13 DepVar1 ~ IndVar1+IndVar2+IndVar3  0.27858393 0.71600105 0.14812808 0.5222330
14 DepVar2 ~ IndVar1+IndVar2+IndVar3  0.15634739 0.08611677 0.02889574 0.7449513