Score scale calculates scale scores.

Usage

score_scale(
  data,
  filter,
  sum = FALSE,
  min_valid = 1,
  max_na = NA,
  label = NULL,
  fun = NULL,
  var_weight = NULL,
  var_recoding = "recodes"
)

Arguments

data: A data frame
filter: A logical expression for any dic attribute (e.g. scale == "ITRF" & subscale == "Int")
sum: If FALSE, a weighted mean function is applied for building the scores. If TRUE, a weighted sum function is applied. When argument fun is set, sum is ignored.
min_valid: Minimal number of valid values that is required for calculating the mean. A value between 0 and 1 indicates a proportion of values (e.g., 0.5 = 50 percent of values have to be valid).
max_na: Maximum number of NAs that are allowed before returning NA. A value between 0 and 1 indicates a proportion of values (e.g., 0.5 = 50 percent NAs are allowed).
label: A character string with a label for the resulting score variable. Automatically generated if label is not set.
fun: A function for calculating the score (e.g., weighted.median). See details.
var_weight: Name of the dic attribute that is applied to derive weights. Defaults to weight.
var_recoding: Name if the dic attribute that may contain recoding information. Defaults to scores.

Value

A data frame

Details

If you provide your own function, the first argument of that function must take the vector of values and the second argument the weights.

Examples

dat <- apply_dic(ex_scaledic_data, ex_scaledic_dic)
#> 
#> 1: Missing values replaced with NA
# apply the default weighted mean function
score_scale(dat, scale == "rel", label = "Religious beliefs")
#> Religious beliefs
#> (weighted mean of items: scale == "rel") 
#> # Data type is numeric
#> # Valid values: From 1 to 5.4
#> # Value labels:
#> #   1 = min
#> #   5.4 = max
#> # Length: 20
#>  [1]  2.20  1.60 15.20  2.60  3.80  3.60  2.40  3.40  4.40  4.80 15.40  3.40
#> [13]  3.80  2.25  2.60  3.80  3.80  4.50  4.20  3.00
# apply the weighted sum function
score_scale(dat, scale == "rel", label = "Religious beliefs", sum = TRUE)
#> Religious beliefs
#> (weighted sum of items: scale == "rel") 
#> # Data type is numeric
#> # Valid values: From 5 to 27
#> # Value labels:
#> #   5 = min
#> #   27 = max
#> # Length: 20
#>  [1] 11  8 76 13 19 18 12 17 22 24 77 17 19  9 13 19 19 18 21 15
# provide an external function (here the weighted median function from the spatstat package)
#score_scale(dat, scale == "rel", label = "Religious beliefs", fun = spatstat.geom::weighted.median)