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

G. Qian; R. M. Huggins; D. Z. Loesch

Discussiones Mathematicae Probability and Statistics (2004)

  • Volume: 24, Issue: 2, page 255-280
  • ISSN: 1509-9423

Abstract

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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.

How to cite

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G. Qian, R. M. Huggins, and D. Z. Loesch. "Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data." Discussiones Mathematicae Probability and Statistics 24.2 (2004): 255-280. <http://eudml.org/doc/287610>.

@article{G2004,
abstract = {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.},
author = {G. Qian, R. M. Huggins, D. Z. Loesch},
journal = {Discussiones Mathematicae Probability and Statistics},
keywords = {pedigree analysis; binary data; MCEM algorithm; Metropolis-Hastings algorithm},
language = {eng},
number = {2},
pages = {255-280},
title = {Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data},
url = {http://eudml.org/doc/287610},
volume = {24},
year = {2004},
}

TY - JOUR
AU - G. Qian
AU - R. M. Huggins
AU - D. Z. Loesch
TI - Application of the Rasch model in categorical pedigree analysis using MCEM: I binary data
JO - Discussiones Mathematicae Probability and Statistics
PY - 2004
VL - 24
IS - 2
SP - 255
EP - 280
AB - 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.
LA - eng
KW - pedigree analysis; binary data; MCEM algorithm; Metropolis-Hastings algorithm
UR - http://eudml.org/doc/287610
ER -

References

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