class.acc {MiscPsycho}R Documentation

Classification Accuracy Statistic: Integration over the Posterior

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. See details below

Details

Function can be used for a mixture of items based on dichotomously scored data and polytomously scored data. The control parameters include:

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)

[Package MiscPsycho version 1.3 Index]