Calculates the D-score and DAZ for each visit — calculate

The function calculate_dscore() calculate the D-score for early child development.

Usage

calculate_dscore(
  txt = "",
  session = "",
  format = "3.1",
  append = c("ddi", "gs1"),
  key = NULL,
  population = NULL,
  output = c("table", "last_visit", "last_dscore"),
  loc = "",
  ...
)

Arguments

txt: A JSON string, URL or file
session: Optional session key if data is already uploaded to sitehost.
format: String. JSON data schema version number. There are currently three schemas supported: "1.0", "1.1", "2.0", "3.0" and "3.1". Formats "1.0" and "1.1" are included for backward compatibility only. Use format = "3.1" for new applications.
append: Optional vector of strings indicating which instrument to base D-score calculations on. Currently supports ddi and gs1. Requires JSON schema V3.0 or later.
key: String. They key identifies 1) the difficulty estimates pertaining to a particular Rasch model, and 2) the prior mean and standard deviation of the prior distribution for calculating the D-score. The default key NULL sets key = "gsed2510". View builtin_keys for an overview of the available keys.
population: String. The name of the reference population to calculate DAZ. Use with(builtin_references, table(key, population)) to see which built-in references are available for key - population combinations. If not specified, the function set the default population as builtin_keys$base_population[key == builtin_keys$key].
output: A string, either "table", "last_visit" or '"last_dscore" specifying the result. The default "table" returns with columns: "date" (date), "x" (age), "y" (D-score) and "z" (DAZ). The number of rows equals to the number of visits. If output equals "last_visit" the function returns only the last row. If output equals "last_dscore" the function returns only the D-score from the last row.
loc: Deprecated. Use session instead.
...: Ignored

Value

A table, row or scalar.

Author

Stef van Buuren 2020-2026

Examples

fn <- system.file("testdata", "Laura_S.json", package = "james")
df <- calculate_dscore(txt = fn)
head(df, 4)
#> [1] a   n   p   d   sem daz
#> <0 rows> (or 0-length row.names)