Using "marg" in a function - how to enquote correctly?-CodePudding

Imagine I have a regression like:

regression <- glm(mpg ~ am * hp, data = mtcars)

I can easily calculate marginal effects with the modmarg package:

library(modmarg)
margins <- marg(
    regression, var_interest = "am",
    at = list("hp" = 52:110),
    type = "effects")

However, I have many models with different variables to compute margins for, so I'd like to put this into a function:

plotting_marg <- function(reg, cov) {
  margins <- marg(
    reg, var_interest = "truth",
    at = list(cov = 52:110),
    type = "effects") 
}
plotting_marg(regression, "hp", -3, 3)

Error in .marg(mod = mod, var_interest = var_interest, data = data, weights = weights,  : 
  var_interest %in% names(data) is not TRUE

This does not work, presumably because cov is not correctly enquoted. I have played around with enquo, but no luck. What is the way to go here?

CodePudding user response：

Naming the list with an object passed can be done with setNames

plotting_marg <- function(reg, cov) {
  marg(
    reg, var_interest = "am",
    at = setNames(list(52:110), cov),
    type = "effects") 
}

-testing

> plotting_marg(regression, "hp")
$`hp = 52`
   Label   Margin Standard.Error Test.Stat    P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN        NaN       0.000000       0.000000
2 am = 1 5.238604       1.918006  2.731276 0.01079466       1.309746       9.167462

$`hp = 53`
   Label   Margin Standard.Error Test.Stat    P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN        NaN       0.000000       0.000000
2 am = 1 5.239007       1.904537  2.750803 0.01030278       1.337739       9.140274

$`hp = 54`
   Label   Margin Standard.Error Test.Stat     P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN         NaN       0.000000       0.000000
2 am = 1 5.239409       1.891116  2.770539 0.009827057       1.365635       9.113184
...

Or may require lst from dplyr/purrr

plotting_marg <- function(reg, cov) {
  marg(
    reg, var_interest = "am",
    at = dplyr::lst(!!cov := 52:110),
    type = "effects") 
}

-testing

> plotting_marg(regression, "hp")
$`hp = 52`
   Label   Margin Standard.Error Test.Stat    P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN        NaN       0.000000       0.000000
2 am = 1 5.238604       1.918006  2.731276 0.01079466       1.309746       9.167462

$`hp = 53`
   Label   Margin Standard.Error Test.Stat    P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN        NaN       0.000000       0.000000
2 am = 1 5.239007       1.904537  2.750803 0.01030278       1.337739       9.140274

$`hp = 54`
   Label   Margin Standard.Error Test.Stat     P.Value Lower CI (95%) Upper CI (95%)
1 am = 0 0.000000       0.000000       NaN         NaN       0.000000       0.000000
2 am = 1 5.239409       1.891116  2.770539 0.009827057       1.365635       9.113184
...