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2004 | 24 | 2 | 255-280
Tytuł artykułu

Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorithm and is illustrated using genotype-phenotype data on a psychological subtest in families where some members are affected by the genetic disorder fragile X. In addition, hypothesis testing and model selection methods based on the Wald statistic are discussed.
Twórcy
autor
  • Department of Statistical Science, La Trobe University, VIC, 3086, Australia
  • Department of Statistical Science, La Trobe University, VIC, 3086, Australia
autor
  • School of Psychological Science, La Trobe University, VIC, 3086, Australia
Bibliografia
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  • [5] S. Chib, Bayesian methods for correlated binary data, Generalized Linear Models, A Bayesian Perspective, Ed. Dey, D.K., Ghosh, S.K., Mallick, B.K. Marcel Dekker, New York (2000), 113-131.
  • [6] S. Chib and E. Greenberg, Understanding the Metropolis-Hastings algorithm, American Statistician 49 (1995), 327-335.
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  • [17] D.Z. Loesch, Q.M. Bui, J. Grigsby, E. Butler, J. Epstein, RM. Huggins and AK. Taylor, Effect of the fragile X status categories and the FMRP levels on executive functioning in fragile X males and females, Neuropsychology (2002) (in press).
  • [18] T.A. Louis, Finding observed information using the EM algorithm, J. Royal Stat. Soc. B 44 (1982), 226-233.
  • [19] X.L. Meng and D.B. Rubin, Using EM to obtain asymptotic variance-covariance matrices: The SEM algorithm, J. Amer. Stat. Assoc. 86 (1991), 899-909.
  • [20] G. Rasch, Probabilistic Models for some Intelligence and Attainment Tests, University of Chicago Press, Chicago 1980.
  • [21] D. Sinha, M.A. Tanner and W.J. Hall, Maximization of the marginal likelihood of grouped survival data, Biometrika 81 (1994), 53-60.
  • [22] S. Sommer and R.M. Huggins, Variable selection using the Wald test and a robust Cp, Applied Statistics 45 (1996), 15-29.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1056
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