subjOCC: ksIRT - kernel smoothing in Item Response Theory

In KernSmoothIRT: Nonparametric Item Response Theory

Description

Returns a list containing a matrix for each item. Each matrix in the list contains a row for each option with each column representing a subject with the probability of selecting that option for each subject.

Usage

subjOCC(x, stype = c("ObsScore","ExpectedScore","MLScore","Theta","MLTheta"))

Arguments

x

a ksIRT object to be analyzed.

stype

the scale on which to evaluate each subject. stype = "ObsScore" uses the subject's observed test score. stype = "ExpectedScore" uses the subject's expected test score.stype = "MLScore" uses the maximum likelihood estimate for the subject's overall score.stype = "Theta" uses the subject's rank on the thetadist scale. stype = "MLTheta" uses the maximum likelihood estimate for the subject on the thetadist scale.

References

Ramsay, J.O. (2000). TestGraf: A program for the graphical analysis of multiple choice test and questionnaire data.

Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.

KernSmoothIRT documentation built on March 26, 2020, 7:42 p.m.