class.acc: Classification Accuracy Statistic: Integration over the...

In wasabi1989/MiscPsycho: Miscellaneous Psychometric Analyses

Description

Computes the probability that individual i has a true score above (or below) cutscore m. In other words, computes the proportion of the posterior distribution that falls above (or below) a cutpoint.

Usage

class.acc(x, prof_cut, params, ind.dichot, aboveC = FALSE, control=list())

Arguments

x	A vector of item responses
prof_cut	Cut score
params	Item parameters organized as a list of lists
ind.dichot	Indicator denoting which items in the vector x are dichotomous
aboveC	Test for above or below a cut score
control	A list of control parameters, D A constant usually fixed at 1.7 to bring the logistic function into coincidence with the probit mu Mean of the prior distribution sigma Standard deviation of the prior distribution Q Number of quadrature points used in the Gauss-Hermite approximation

Value

prob	Returns the probability that individual i has a true score above (or below) the cut score specified

Author(s)

Harold C. Doran

Examples

a <- c(1.45, 1.84, 2.55, 2.27, 3.68, 4.07, 2.26, 1.87, 2.19, 1.33)
b <- c(-.6, -.82, -1.6, -.87, -1.41, -1.33, -1.16, -.11, -.64, -1.23)
params <- list("3pl" = list(a = a, b = b, c = rep(0, 10)), 
               "gpcm" = NULL)
x <- c(rep(0,9),1)
class.acc(x, prof_cut = 0, params, ind.dichot = c(1:10), aboveC=TRUE)

wasabi1989/MiscPsycho documentation built on Jan. 19, 2020, 12:29 a.m.