Advanced SearchSearch Tips
Development of Estimation Algorithm of Latent Ability and Item Parameters in IRT
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Development of Estimation Algorithm of Latent Ability and Item Parameters in IRT
Choi, Hang-Seok; Cha, Kyung-Joon; Kim, Sung-Hoon; Park, Chung; Park, Young-Sun;
  PDF(new window)
Item response theory(IRT) estimates latent ability of a subject based on the property of item and item parameters using item characteristics curve(ICC) of each item case. The initial value and another problems occurs when we try to estimate item parameters of IRT(e.g. the maximum likelihood estimate). Thus, we propose the asymptotic approximation method(AAM) to solve the above mentioned problems. We notice that the proposed method can be thought as an alternative to estimate item parameters when we have small size of data or need to estimate items with local fluctuations. We developed 'Any Assess' and tested reliability of the system result by simulating a practical use possibility.
Item response theory(IRT);item characteristics curve(ICC);initial value problem;asymptotic approximation method(AAM);
 Cited by
박영선, 차경준, 장창원 (2003a).IRT 모수추정에서 초기값에 관한 연구, <한국통계학회 2003년 춘계학술발표회 논문집>, 7-12

박영선, 진정언, 차경준, 이종성, 박정, 김성훈, 이원식, 이재화 (2003b). IRT에서 피험자 능력 및 문항모수 추정 알고리즘 개발, <한국통계학회 2003년 추계학술발표회 논문집>, 149-154

성태제 (1994). 대학별고사를 위한 문항분석, 표준점수, 검사동등화, <한국통계학회 논문집>, 1, 206-214

이종성 (1990). <문항반응이론과 응용>, 대광문화사

Andersen, E. B. (1970). Asymptotic properties of conditional maximum-likelihood estimators, Journal of the Royal Statistical Society, Ser. B, 32, 283-301

Baker, F. B. (1992). Item Response Theory: Parameter Estimation Technique, Marcel Dekker, New York

Birnbaum, A. (1968). Test scores, su$\pm$cient statistics, and the information structures of tests. In Lord, F. M. and Novick, M. R., Statistical Theories of Mental Testscores, Reading, Mass.: Addison & Wesley

Bock, R. D. and Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm, Psychometrika, 46, 443-459 crossref(new window)

Bock, R. D. and Lieberman, M. (1970). Fitting a response model for n dichotomously scored items. Psychometrika, 35, 179-197 crossref(new window)

Cohen, A. S., Bottge, B. A. andWells, C. S. (2001). Using item response theory to assess effects of mathematics instruction in special populations, Exceptional Childeren, 68 23-44 crossref(new window)

Craven, P. and Wahba, G. (1977). Smoothing Noisy Data with Spline Functions: Estimating the Correct Degree of Smoothing by the Method of Generalized CrossValidation. Technical Report No. 445, Madison, Department of Statistics, University of Wisconsin

Foutz, R. V. (1977). On the unique consistent solution to the likelihood equations, Journal of the American Statistical Association, 72, 147-148 crossref(new window)

Hambleton, R. K. and Cook, L. L. (1977). Latent trait models and their use in the analysis of educational test data, Journal of Education Measurement, 14, 75-96 crossref(new window)

Kale, B. K. (1962). On the solution of likelihood equations by iteration processes. The multiparametric case, Biometrika, 49, 479-486 crossref(new window)

Lee, S. and Terry, R. (2005). IRT-FIT: SAS macros for fitting item response theory(IRT) models, Presented at SUGI 30th Conference in Philadelphia

Looney, M. A. and Spray, J. A. (1992). Effects of violating local independence on IRT parameter estimation for the Binomial Trials model, Research Quarterly for Exercise and Sport, 63, 356-359 crossref(new window)

Lord, F. M. (1953). Estimation of latent ability and item parameters when there are omitted responses, Psychometrika, 39, 247-264 crossref(new window)

Lord, F. M.(1983). Statistical bias in maximum likelihood estimators of item parameters, Psychometrika, 48. 425-435 crossref(new window)

Mislevy, R. J. and Bock, R. D. (1990). BILOG 3: Item Analysis and Test Scoring with Binary Logistic Model , Mooresville IN: Scientific Software, Inc

Mislevy, R. J. and Wu, P. K. (1988). Inferring Examinee Ability When Some Item Responses are Missing, (Research Report 88-48-ONR), Princeton, N.J.: Educational Testing Service

Muraki, E. (2000). RESGEN: A Computer Program to Generate Item Response Vector,Princeton: ETS

Samejima, F. (1973). A comment on Birnbaum's three-parameter logistic model in the latent trait theory, Psychomtrika, 38, 221-233 crossref(new window)

Stocking, M., Wingersky, M. S., Lees, D. M., Lennon, V. and Lord, F. M. (1973). A Program for Estimating the Relative Effciency of Tests at Various Ability Levels, for Equating True Scores and for Predicting Bivariate Distributions of Observed Socres, Research Memorandum 73-24, Princeton, N.J.: Educational Testing Service

waminathan, H. and Gifford, J. A. (1986). Bayesian estimation in the three-parameter logistic model, Psychometrika, 51, 589-601 crossref(new window)

Thissen, D. and Wainer, H. (1982). Some standard errors in item response theory, Psychometrika, 47, 397-412 crossref(new window)

Wingersky, M. S., Barton, M. A. and Lord, F. M.(1982). LOGIST user's guide, Princeton, NJ: Educational Testing Service

Wollack, J. A., Bolt, D. M., Cohen, A. S., Lee, Y. S. (2002). Recovery of item parameters in the nominal response model: A comparision of marginal maximum likelihood estimation and Markov chain Monte Carlo estimation, Applied Psychological Measurement, 26, 339-351 crossref(new window)