null_repsd {repsd}

null_repsd

Description

null_repsd

Usage

null_repsd(
  item_count = 20,
  focal_sample = 88,
  focal_prop = 0.09,
  numStrata = 4,
  impact = estimate_impact(),
  item_params_a = timmsDiscrim,
  item_params_b = timmsDiffic,
  anchorItems = NULL,
  iterations = 10000,
  verbose = TRUE
)

Arguments

item_count

numeric. How many items?

focal_sample

numeric. How large is the focal sample?

focal_prop

numeric, between 0 and 1 (exclusive). What is the proportion of the focal sample compared to the rest of the data?

numStrata

numeric. How many strata for matching should be used?

impact

numeric. What is the expected, standardized mean difference between the focal group's mean theta and the composite group's mean theta (i.e., standardized focal mean - composite mean). See details for further explanation.

item_params_a

numeric vector. What are the discrimination parameters of the items in the data set?

item_params_b

numeric vector. What are the difficulty parameters of the items in the data set?

anchorItems

either NULL or a vector of the anchorItems names or numeric column locations. If NULL, all items are used for calculating the total test score for stratifying individuals. If a vector, the specified items are used to calculate the total test score for stratifying individuals.

iterations

numeric. How many iterations for the function to run? Defaults to 10000.

verbose

logical. If TRUE (default), prints a progress::progress_bar() in the console to allow tracking of the state of the distribution generation.

Value

An item_count x iterations data.frame with simulated repsd values for each item.