메뉴 건너뛰기




Volumn 74, Issue 4, 2009, Pages 633-665

Cluster analysis for cognitive diagnosis: Theory and applications

Author keywords

Cluster analysis; Cognitive diagnosis; Latent class analysis

Indexed keywords


EID: 77949264952     PISSN: 00333123     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11336-009-9125-0     Document Type: Article
Times cited : (175)

References (40)
  • 1
    • 58149411423 scopus 로고
    • Mixture model tests of cluster analysis: Accuracy of four agglomerative hierachical methods
    • Blashfield, P. K. (1976). Mixture model tests of cluster analysis: accuracy of four agglomerative hierachical methods. Psychological Bulletin, 83, 377-385.
    • (1976) Psychological Bulletin , vol.83 , pp. 377-385
    • Blashfield, P.K.1
  • 4
    • 0002346896 scopus 로고
    • Evaluation of hierachical grouping techniques: A preliminary study
    • Cunnningham, K. M., & Ogilvie, J. C. (1972). Evaluation of hierachical grouping techniques: A preliminary study. Computer Journal, 15, 209-213.
    • (1972) Computer Journal , vol.15 , pp. 209-213
    • Cunnningham, K.M.1    Ogilvie, J.C.2
  • 5
    • 12344281031 scopus 로고    scopus 로고
    • Higher order latent trait models for cognitive diagnosis
    • de la Torre, J., & Douglas, J. A. (2004). Higher order latent trait models for cognitive diagnosis. Psychometrika, 69, 333-353.
    • (2004) Psychometrika , vol.69 , pp. 333-353
    • de la Torre, J.1    Douglas, J.A.2
  • 6
    • 0002301969 scopus 로고    scopus 로고
    • Multicomponent response models
    • W. J. Lindenvan der and R. K. Hambleton (Eds.), New York: Springer
    • Embretson, S. (1997). Multicomponent response models. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 305-321). New York: Springer.
    • (1997) Handbook of Modern Item Response Theory , pp. 305-321
    • Embretson, S.1
  • 8
    • 0000014486 scopus 로고
    • Cluster analysis of multivariate data: Efficiency versus interpretability of classifications
    • Forgy, E. W. (1965). Cluster analysis of multivariate data: Efficiency versus interpretability of classifications. Biometrics, 21, 768-769.
    • (1965) Biometrics , vol.21 , pp. 768-769
    • Forgy, E.W.1
  • 9
    • 0000637050 scopus 로고
    • Asymptotic distributions for clustering criteria
    • Hartigan, J. A. (1978). Asymptotic distributions for clustering criteria. The Annals of Statistics, 6, 117-131.
    • (1978) The Annals of Statistics , vol.6 , pp. 117-131
    • Hartigan, J.A.1
  • 10
    • 84988128977 scopus 로고
    • Using restricted latent class models to map the skill structure of achievement items
    • Haertel, E. H. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26, 333-352.
    • (1989) Journal of Educational Measurement , vol.26 , pp. 333-352
    • Haertel, E.H.1
  • 11
    • 0000440128 scopus 로고
    • A Monte Carlo study of the recovery of cluster structure in binary data by hierarchical clustering techiniques
    • Hands, S., & Everitt, B. S. (1987). A Monte Carlo study of the recovery of cluster structure in binary data by hierarchical clustering techiniques. Multivariate Behavioural Research, 22, 235-243.
    • (1987) Multivariate Behavioural Research , vol.22 , pp. 235-243
    • Hands, S.1    Everitt, B.S.2
  • 14
    • 77949267010 scopus 로고    scopus 로고
    • Paper presented at the Annual Meeting of the National Council on Measurement in Education, Chicago, IL
    • Henson, R., & Templin, J. (2007). Paper presented at the Annual Meeting of the National Council on Measurement in Education, Chicago, IL.
    • (2007)
    • Henson, R.1    Templin, J.2
  • 15
    • 84947403595 scopus 로고
    • Probabilistic inequalities for sums of bounded random variables
    • Hoeffding, W. (1963). Probabilistic inequalities for sums of bounded random variables. Annals of Mathematical Statistics, 58, 13-30.
    • (1963) Annals of Mathematical Statistics , vol.58 , pp. 13-30
    • Hoeffding, W.1
  • 17
    • 0035536719 scopus 로고    scopus 로고
    • Cognitive assessment models with few assumptions, and connections with nonparametric item response theory
    • Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258-272.
    • (2001) Applied Psychological Measurement , vol.25 , pp. 258-272
    • Junker, B.W.1    Sijtsma, K.2
  • 19
    • 0016784903 scopus 로고
    • A Monte Carlo comparison of six clustering procedures
    • Kuiper, F. K., & Fisher, L. (1975). A Monte Carlo comparison of six clustering procedures. Biometrics, 31, 777-783.
    • (1975) Biometrics , vol.31 , pp. 777-783
    • Kuiper, F.K.1    Fisher, L.2
  • 22
    • 0001457509 scopus 로고
    • Some methods of classification and analysis of multivariate observations
    • L. M. CamLe and J. Neyman (Eds.), Berkeley: University of California Press
    • MacQueen, J. (1967). Some methods of classification and analysis of multivariate observations. In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the fifth Bekeley Symposium on Mathematical Statistics and Probability (pp. 281-207). Berkeley: University of California Press.
    • (1967) Proceedings of the Fifth Bekeley Symposium on Mathematical Statistics and Probability , pp. 281-207
    • Macqueen, J.1
  • 23
    • 12344330072 scopus 로고
    • The use of probabilistic models in the assessment of mastery
    • Macready, G. B., & Dayton, C. M. (1977). The use of probabilistic models in the assessment of mastery. Journal of Educational Statistics, 33, 379-416.
    • (1977) Journal of Educational Statistics , vol.33 , pp. 379-416
    • Macready, G.B.1    Dayton, C.M.2
  • 24
    • 0033239548 scopus 로고    scopus 로고
    • Estimating multiple classification latent class models
    • Maris, E. (1999). Estimating multiple classification latent class models. Psychometrika, 64, 187-212.
    • (1999) Psychometrika , vol.64 , pp. 187-212
    • Maris, E.1
  • 25
    • 33847457966 scopus 로고
    • An examination of the effects of six types of error perturbation on fifteen clustering algorithms
    • Milligan, G. W. (1980). An examination of the effects of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45, 325-342.
    • (1980) Psychometrika , vol.45 , pp. 325-342
    • Milligan, G.W.1
  • 27
    • 0033204902 scopus 로고    scopus 로고
    • An empirical comparison of four initialization methods for the K-means algorithm
    • Pena, J., Lozano, J., & Larranaga, P. (1999). An empirical comparison of four initialization methods for the K-means algorithm. Pattern Recognition Letters, 20, 1027-1040.
    • (1999) Pattern Recognition Letters , vol.20 , pp. 1027-1040
    • Pena, J.1    Lozano, J.2    Larranaga, P.3
  • 28
    • 0000963889 scopus 로고
    • Strong consistency of K-means clustering
    • Pollard, D. (1981). Strong consistency of K-means clustering. The Annals of Statistics, 9(1), 135-140.
    • (1981) The Annals of Statistics , vol.9 , Issue.1 , pp. 135-140
    • Pollard, D.1
  • 30
    • 0000470917 scopus 로고
    • Cluster analysis in marketing research: A review and suggestions for application
    • Punj, G., & Stewart, D. W. (1983). Cluster analysis in marketing research: A review and suggestions for application. Journal of Marketing Research, 20, 134-148.
    • (1983) Journal of Marketing Research , vol.20 , pp. 134-148
    • Punj, G.1    Stewart, D.W.2
  • 32
    • 0142136684 scopus 로고    scopus 로고
    • Local optima in k-means clustering: What you don't know may hurt you
    • Steinley, D. (2003). Local optima in k-means clustering: What you don't know may hurt you. Psychological Methods, 8, 294-304.
    • (2003) Psychological Methods , vol.8 , pp. 294-304
    • Steinley, D.1
  • 34
    • 0036425097 scopus 로고    scopus 로고
    • Data-analytic methods for latent partially ordered classification models
    • Tatsuoka, C. (2002). Data-analytic methods for latent partially ordered classification models. Applied Statistics (JRSS-C), 51, 337-350.
    • (2002) Applied Statistics (JRSS-C) , vol.51 , pp. 337-350
    • Tatsuoka, C.1
  • 35
    • 0010785646 scopus 로고
    • A probabilistic model for diagnosing misconceptions in the pattern classification approach
    • Tatsuoka, K. (1985). A probabilistic model for diagnosing misconceptions in the pattern classification approach. Journal of Educational Statistics, 12, 55-73.
    • (1985) Journal of Educational Statistics , vol.12 , pp. 55-73
    • Tatsuoka, K.1
  • 36
    • 33748759826 scopus 로고    scopus 로고
    • Measurement of psychological disorders using cognitive diagnosis models
    • Templin, J. L., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11, 287-305.
    • (2006) Psychological Methods , vol.11 , pp. 287-305
    • Templin, J.L.1    Henson, R.A.2
  • 39
    • 84944178665 scopus 로고
    • Hierarchical Grouping to optimize an objective function
    • Ward, J. H. (1963). Hierarchical Grouping to optimize an objective function. Journal of the American Statistical Association, 58, 236-244.
    • (1963) Journal of the American Statistical Association , vol.58 , pp. 236-244
    • Ward, J.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.