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Volumn 11, Issue 1, 2010, Pages 1-10

Predicting responses from rasch measures

Author keywords

[No Author keywords available]

Indexed keywords

BOLTZMANN MACHINES; CURRENT DATA; DATA SETS; MODEL PARAMETERS; POLYTOMOUS; PREDICTIVE POWER;

EID: 77951632726     PISSN: 15297713     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review
Times cited : (32)

References (16)
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    • Ackley, D.1    Hinton, G.2    Sejnowski, T.3
  • 2
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    • Information theory as an extension of the maximum likelihood principle
    • B. N. Petrov and F. Csaksi, (Eds.). Budapest, Hungary: Akademiai Kiado.
    • nd International Symposium on Information Theory (pp. 267-281). Budapest, Hungary: Akademiai Kiado.
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    • Akaike, H.1
  • 3
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    • Sufficient statistics and latent trait models
    • Andersen, E. B. (1977). Sufficient statistics and latent trait models. Psychometrika, 42, 69-81.
    • (1977) Psychometrika , vol.42 , pp. 69-81
    • Andersen, E.B.1
  • 4
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    • A rating formulation for ordered response categories
    • Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43, 357-74.
    • (1978) Psychometrika , vol.43 , pp. 357-374
    • Andrich, D.1
  • 5
    • 79955809803 scopus 로고    scopus 로고
    • Bbame (pseudonym). March 14. Retrieved on January 19, 2008, from
    • Bbame (pseudonym). (2007, March 14). Movie metadata. Retrieved on January 19, 2008, from http://www.netflixprize.com
    • (2007) Movie Metadata.
  • 7
    • 79955797238 scopus 로고    scopus 로고
    • Retrieved January 19, 2008, from
    • Dirks, T. (2008). Film genres. Retrieved January 19, 2008, from http://www.filmsite.org/genres.html
    • (2008) Film Genres
    • Dirks, T.1
  • 10
    • 0031635498 scopus 로고    scopus 로고
    • Detecting multidimensionality: Which residual data-type works best?
    • Linacre, J. M. (1998). Detecting multidimensionality: Which residual data-type works best? Journal of Outcome Measurement, 2, 266-283.
    • (1998) Journal of Outcome Measurement , vol.2 , pp. 266-283
    • Linacre, J.M.1
  • 11
    • 0000261668 scopus 로고
    • A Rasch model for partial credit scoring
    • Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149-174.
    • (1982) Psychometrika , vol.47 , pp. 149-174
    • Masters, G.N.1
  • 13
    • 0442315448 scopus 로고    scopus 로고
    • The growing family of Rasch models
    • A. Boomsma, M. van Duijn, and T. Snijders (Eds.), Berlin/Heidelberg/New York: Springer.
    • Rost, J. (2001). The growing family of Rasch models. In A. Boomsma, M. van Duijn, and T. Snijders (Eds.), Essays on item response theory. Berlin/Heidelberg/New York: Springer.
    • (2001) Essays on Item Response Theory
    • Rost, J.1
  • 14
    • 0000329993 scopus 로고
    • Information processing in dynamical systems: Foundations of harmony theory
    • D. E. Rumelhart and J. L. McClelland (Eds.). Cambridge, MA: MIT Press.
    • Smolensky, P. (1986). Information processing in dynamical systems: Foundations of harmony theory. In D. E. Rumelhart and J. L. McClelland (Eds.). Parallel distributed processing: Foundations (Vol. 1, pp. 194-281). Cambridge, MA: MIT Press.
    • (1986) Parallel Distributed Processing: Foundations , vol.1 , pp. 194-281
    • Smolensky, P.1
  • 15
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    • A steps model to analyze partial credit
    • W. J. van der Linden and R. K. Hambleton (Eds.), New York: Springer.
    • Verhelst, N. D., Glas, C. A. W., and De Vries, H. H. (1997). A steps model to analyze partial credit. In W. J. van der Linden and R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 123-138) New York: Springer.
    • (1997) Handbook of Modern Item Response Theory , pp. 123-138
    • Verhelst, N.D.1    Glas, C.A.W.2    De Vries, H.H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.