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한국통계학회 논문집 = Communications of the Korean Statistical Society, v.15 no.3, 2008년, pp.465 - 481
최항석 (삼성생명과학연구소 유전체연구센터) , 차경준 (한양대학교 수학과) , 김성훈 (동국대학교 교육학과) , 박정 (부산대학교 유아교육학과) , 박영선 (한양대학교 수학과)
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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...
박영선, 차경준, 장창원 (2003a).IRT 모수추정에서 초기값에 관한 연구, , 7-12
박영선, 진정언, 차경준, 이종성, 박정, 김성훈, 이원식, 이재화 (2003b). IRT에서 피험자 능력 및 문항모수 추정 알고리즘 개발, , 149-154
이종성 (1990). , 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
Bock, R. D. and Lieberman, M. (1970). Fitting a response model for n dichotomously scored items. Psychometrika, 35, 179-197
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
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
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
Kale, B. K. (1962). On the solution of likelihood equations by iteration processes. The multiparametric case, Biometrika, 49, 479-486
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
Lord, F. M. (1953). Estimation of latent ability and item parameters when there are omitted responses, Psychometrika, 39, 247-264
Lord, F. M.(1983). Statistical bias in maximum likelihood estimators of item parameters, Psychometrika, 48. 425-435
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
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
Thissen, D. and Wainer, H. (1982). Some standard errors in item response theory, Psychometrika, 47, 397-412
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
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