I'm trying to write a function called item_pool which takes an arbitrary function, L1F, as a parameter. How would I get L1F to work in dplyr::mutate within the item_pool function? Please see the following.

#Define item_pool function
item_pool <- function(df,
                      L1F,
                      w){
  x <- w
  
  df %>%
    dplyr::mutate(L1_Items = L1F)
}

#Create data frame
df_ul1 <- data.frame(domain = 1:4,
                     y = c(.25, .25, .25, .25),
                     z = c(.25, .25, .25, .25))

#Create L1_Items variable based on L1F function
df_ul1_ip <- item_pool(df = df_ul1,
                       L1F = (function(x,y,z){x*mean(y, z)})(x,y,z),
                       w = 20)

For context, this is a small snippet of a function which assigns the number of item pool items to write for each domain (or other structures such items per task within domain) based on a set of standards (i.e., minimum number of items per domain, target test length [w], number of forms, item pool/test length ratio, weights, etc.).

CodePudding user response：

There are a few modifications

1. If you want to pass the function directly, you only need function(...){}, not function(...){}(...)
2. To take a mean of two variables at each row, mean(y, z) will not work. One way to do that is use rowMeans
3. Move x <- w inside the L1F function call
   • This is just a style choice

library(dplyr, warn = FALSE)

#Define item_pool function
item_pool <- function(df,
                      L1F,
                      w){
  df %>%
    dplyr::mutate(L1_Items = L1F(x = w, y, z))
}

#Create data frame
df_ul1 <- data.frame(domain = 1:4,
                     y = c(.25, .25, .25, .25),
                     z = c(.25, .25, .25, .25))

#Create L1_Items variable based on L1F function
df_ul1_ip <- item_pool(df = df_ul1,
                       L1F = function(x,y,z){ x * rowMeans(cbind(y, z)) },
                       w = 20)

df_ul1_ip
#>   domain    y    z L1_Items
#> 1      1 0.25 0.25        5
#> 2      2 0.25 0.25        5
#> 3      3 0.25 0.25        5
#> 4      4 0.25 0.25        5

^{Created on 2022-09-16 with reprex v2.0.2}