ksIRT - kernel smoothing in Item Response Theory


This function 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.


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



a ksIRT object to be analyzed.


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.


Ramsay, J.O. (2000). TestGraf: A program for the graphical analysis of multiple choice test and questionnaire data. http://www.psych.mcgill.ca/faculty/ramsay/ramsay.html.

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

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.

comments powered by Disqus