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Check for Unsystematic Data Violations

Source: R/utils.R
check_unsystematic.Rd

This function checks a dataset for violations of two criteria commonly used to identify unsystematic delay-discounting data:

  • Criterion 1: Any subsequent value of y exceeds the previous value by more than a specified proportion of the larger later reward (ll).

  • Criterion 2: The last value of y is not at least a specified proportion less than the first value of y.

Usage

check_unsystematic(dat, ll = 1, c1 = 0.2, c2 = 0.1)

Arguments

dat

A data frame containing the delay-discounting data. It must have at least two columns:

  • id: A unique identifier for the data set.

  • y: The indifference points to be analyzed.

  • x (optional): Delay values; when present, each subject's points are ordered by delay first.

ll

A numeric value representing the larger later reward. Default is 1.

c1

A numeric value for the threshold proportion for Criterion 1. Default is 0.2.

c2

A numeric value for the threshold proportion for Criterion 2. Default is 0.1.

Value

A tibble with the following columns:

  • id: The unique identifier for the data set.

  • c1_pass: Logical value indicating whether Criterion 1 was passed.

  • c2_pass: Logical value indicating whether Criterion 2 was passed.

Details

The criteria are applied separately to each id, so a data frame containing several subjects returns one row per subject. When an x (delay) column is present, each subject's points are ordered by delay before the criteria are applied.

Examples

data <- tibble::tibble(
  id = c(rep("P1", 6)),
  x = c(1, 7, 30, 90, 180, 365), # delays
  y = c(0.9, 0.5, 0.3, 0.2, 0.1, 0.05) # indifference points
)
check_unsystematic(data, ll = 1, c1 = 0.2, c2 = 0.1)
#> # A tibble: 1 × 3
#>   id    c1_pass c2_pass
#>   <chr> <lgl>   <lgl>  
#> 1 P1    TRUE    TRUE