Score a set of factors by counting their first level

Builds an integer score column counting, for each row, how many of the listed factors sit at their first level (1 if so, 0 otherwise) – the score ranges 0 to length(vars_list). The natural way to sum a battery of yes/no survey items into one score, feeding the grouped-binomial outcome of tab_reg() (its trials argument).

Usage

score_from_lv1(data, name, vars_list)

Arguments

data

A data.frame.

name

The name of the score variable to create (unquoted or a string); an existing column of that name is replaced.

vars_list

The factors to count, as a character vector. For each one only its first level counts (as 1); every other level, including missing values, counts as 0.

Value

data with the integer score column name added (or replaced).

Details

The "first level" is levels(as.factor(x))[1]. Non-factor columns are coerced with as.factor(); missing values are folded into an explicit "NA" level first (via forcats::fct_na_value_to_level()), so NA never counts as the first level.

See also

tab_reg() and its trials argument for modelling a summed score as a grouped binomial; vignette("tabxplor"), section "Multiple-answer questions", for a worked example.

Examples

data <- tibble::tibble(group = factor(c("G1", "G1", "G2", "G2", "G3", "G3")),
                       a = factor(c("Oui", "Oui", "Oui", "Oui", "Non", "Oui")),
                       b = factor(c("Oui", "Non", "Non", "Oui", "Non", "Oui")),
                       c = factor(c("Oui", "Oui", "Non", "Non", "Oui", "Oui")))
data |>
  score_from_lv1("score", vars_list = c("a", "b", "c")) |>
  tab(group, score, digits = 1)
#> # A tabxplor tab: 4 × 2
#>   group          score
#>            <mean (cv)>
#> 1 G1     0.5 (cv 141%)
#> 2 G2     1.5 (cv  47%)
#> 3 G3     1.0 (cv 141%)
#> 4 Total  1.0 (cv  89%)