Adjusts observed 1s based on item level parameters of the LCA model. Currently only takes data with Don't Know. And treats don't know responses as true confessions on ignorance. By default, NAs are treated as acknowledgments of ignorance.

lca_adj(
  pre = NULL,
  pst = NULL,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

Arguments

pre

pre data frame

pst

pst data frame

na_as

Classification of NA responses: `"dk"` (the default) treats them as observed don't know responses; `"missing"` treats them as structural missingness.

missing_action

How to handle structural missingness: `"omit"` excludes it and `"error"` rejects it.

Value

list of pre and post adjusted responses

Examples

pre_test_var <- data.frame(pre = c(1, 0, 0, 1, "d", "d", 0, 1, NA))
pst_test_var <- data.frame(pst = c(1, NA, 1, "d", 1, 0, 1, 1, "d"))
lca_adj(pre_test_var, pst_test_var)
#> $pre
#>       pre                   
#>  [1,] "0.000369644514660049"
#>  [2,] "0"                   
#>  [3,] "0"                   
#>  [4,] "0.000369644514660049"
#>  [5,] "0"                   
#>  [6,] "0"                   
#>  [7,] "0"                   
#>  [8,] "0.000369644514660049"
#>  [9,] "0"                   
#> 
#> $pst
#>       pst                
#>  [1,] "0.800128113753964"
#>  [2,] "0"                
#>  [3,] "0.800128113753964"
#>  [4,] "0"                
#>  [5,] "0.800128113753964"
#>  [6,] "0"                
#>  [7,] "0.800128113753964"
#>  [8,] "0.800128113753964"
#>  [9,] "0"                
#>