item_gen: Generation of item parameters from uniform distributions

In tmatta/lsasim: Functions to Facilitate the Simulation of Large Scale Assessment Data

Generation of item parameters from uniform distributions

Description

Creates a data frame of item parameters.

Usage

item_gen(
  b_bounds,
  a_bounds = NULL,
  c_bounds = NULL,
  thresholds = 1,
  n_1pl = NULL,
  n_2pl = NULL,
  n_3pl = NULL
)

Arguments

b_bounds	a vector containing the bounds of the the uniform distribution for sampling the difficulty parameters.
a_bounds	a vector containing the bounds of the the uniform distribution for sampling the discrimination parameters.
c_bounds	a vector containing the bounds of the the uniform distribution for sampling the guessing parameters.
thresholds	if numeric, number of thresholds for 1- and/or 2- parameter dichotomous items, if vector, each element is the number of thresholds corresponding to the vector of n_1pl and/or n_2pl.
n_1pl	if integer, number of 1-parameter dichotomous items, if vector, each element is the number of partial credit items corresponding to thresholds number.
n_2pl,	if integer, number of 2-parameter dichotomous items, if vector, each element is the number of generalized partial credit items corresponding to thresholds number.
n_3pl	integer, number of 3-parameter items.

Details

The data frame includes two variables p and k which indicate the number of parameters and the number of thresholds, respectively

Examples

item_gen(b_bounds = c(-2, 2), a_bounds = c(.75, 1.25),
  thresholds = c(1, 2, 3), n_1pl = c(5, 5, 5), n_2pl = c(0, 0, 5))
item_gen(b_bounds = c(-2, 2), a_bounds = c(.75, 1.25), c_bounds = c(0, .25),
  n_2pl = 5, n_3pl = 5)

tmatta/lsasim documentation built on Aug. 25, 2023, 5:50 p.m.