CPRV: This function calculates the conditional proportion reduction...

In mustfa5/test.adaptation: Adaptation - level of adaptation of a computerized adaptive test

Description

This function calculates the conditional proportion reduction in variance (PRV) index as described in Ju and Reckase (2019)

Usage

CPRV(diff, bank)

Arguments

diff	a data frame in which rows represent test takers while columns represent the difficulty level of items that were administered to that test taker
bank	A data matrix that have item parameters in the following order: discrimination, difficulty, guessing and slipping.#'

Value

This function returns a matrix of CPRV values in numeric form

References

Ju, U., & Reckase, M. D. (2019). New conditional measures of the amount of adaptation of adaptive tests. Paper presented at the annual meeting of the National Council on Measurement in Education, Toronto, Canada.

Examples

library(catR)
N=1000 #number of students
bank=250 #number of items
items=45
theta=rnorm(N,0,1) #level of trait
model="2PL" #IRT model to use
start <- list(theta = -1:1, randomesque = 1)
stop <- list(rule = c( "length"), thr = items)
final <- list(method = "ML")

test=list(method = "ML", itemSelect = "MFI")
bank=genDichoMatrix(items =bank, cbControl = NULL,
                    model = model)

res <- simulateRespondents(thetas = theta, bank,
                           start = start, test = test, stop = stop,
                           final = final, model = NULL)
t.hat=res$final.values.df$estimated.theta

items.administered=res$responses.df[,grepl("items.administrated",
                                           names( res$responses.df ) ) ]
colnames(items.administered)=NULL
diff=matrix(ncol = ncol(items.administered),nrow = nrow(items.administered))
for (k in 1:nrow(items.administered)) {
  xx= as.numeric(items.administered[k,])
  diff[k,]=bank[xx,2]
}
CPRV(diff = diff, bank=bank )

mustfa5/test.adaptation documentation built on Dec. 21, 2021, 11:03 p.m.