SD.ratio: This function calculates the ratio of standard deviations...

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

Description

This function calculates the ratio of standard deviations index as described in Reckase, Ju, and Kim (2019)

Usage

SD.ratio(item.diff, theta.hat)

Arguments

item.diff	average item difficulties administered to a test taker during a computerized test administration
theta.hat	estimated ability level of a group of individuals who were measured using a CAT environment

Value

This function returns numeric value

References

Reckase, M. D., Ju, U., & Kim, S. (2019). How adaptive is an adaptive test: Are all adaptive tests adaptive?. Journal of Computerized Adaptive Testing, 7(1), 1-14.

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)
theta.hat=res$final.values.df$estimated.theta

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

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