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,
- 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 1.5
Index]