The full-information item factor analysis model pro posed by Bock and Aitkin (1981) is described, and some of the characteristics of expected a posteriori (EAP) scores are illustrated. Three simulation studies were conducted to illustrate the model, and an appli cation of full-information item factor analysis to a set of real data is described.
Get full access to this article
View all access options for this article.
References
1.
Ahrens, J.H., & Dieter, U. (1972). Computer methods for sampling from the exponential and normal distributions. Communications of the ACM, 15, 873-882.
2.
Bartholomew, D.J. (1980). Factor analysis for categorical data. Journal of the Royal Statistical Society, Series B, 42, 293-321.
3.
Bock, R.D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika , 46, 443-458.
4.
Bock, R.D., Gibbons, R., & Muraki, E. (1985). Full-information item factor analysis. Chicago: National Opinion Research Center .
5.
Bock, R.D., & Mislevy, R.J. (1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psychological Measurement, 6, 431-444.
6.
Bock, R.D., Mislevy, R.J., & Woodson, C. (1982). The next stage in educational assessment. Educational Researcher, 11 (3), 4-11.
7.
Campbell, A., Converse, P.E., & Rodgers, W.L. (1976). The quality of life. New York : Russel Sage Foundation.
8.
Carroll, J.B. (1945). The effect of difficulty and chance success on correlations between items or between tests. Psychometrika , 10, 1-19.
9.
Christoffersson, A. (1975). Factor analysis of dichotomized variables. Psychometrika, 40, 5-32.
10.
Dempster, A.P., Laird, N.M., & Rubin, D.B. (1977). Maximum likelihood from incomplete data with the EM algorithm (with discussion). Journal of the Royal Statistical Society, Series B, 34, 1-34.
Engelhard, G. (1985). The discovery of educational goals and outcomes: A view of the latent curriculum of schooling. Unpublished doctoral dissertation, The University of Chicago.
13.
Haberman, J.S. (1977). Log-linear models and frequency tables with small expected cells counts. Annals of Statistics, 5, 1148-1169.
14.
Harman, H.H. (1976). Modern factor analysis. Chicago : The University of Chicago Press.
15.
Kaiser, H.F. (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrika, 23, 187-200.
16.
Mislevy, R.J., & Bock, R.D. (1984). Item operating characteristics of the Armed Services Vocational Aptitude Battery (ASVAB), Form 8A. Chicago: National Opinion Research Center.
17.
Muraki, E., & Engelhard, G. (1985, March). Affective outcomes of schooling: Full-information item factor analysis of a student questionnaire. Paper presented at the annual meeting of the American Educational Research Association in Chicago.
18.
Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43, 551-560.
19.
Muthén, B. (1984). A general structural equation model with dichotomous, ordered categories, and continuous latent variable indicators. Psychometrika, 49, 115-132.
20.
Schrage, L. (1979). A more portable Fortran random generator. ACM Transaction Mathematical Software, 5, 132-138.
Wilson, D., Wood, R.L., & Gibbons, R. (1984). TEST-FACT: Test scoring and item factor analysis [Computer program]. Mooresville IN: Scientific Software, Inc.
