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Statistical inference for familial disease models assuming exchangeability

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  • Bowman, Dale

Abstract

Binary data often occur in epidemiology studies clustered by families. When an assumption of exchangeability of response is reasonable, the exchangeable multinomial distribution may be used to model binary and multinomial responses. Conditional probabilities of a new family member being diagnosed given family members previously diagnosed are derived. Applications are made to real familial disease data on IPF and ALS.

Suggested Citation

  • Bowman, Dale, 2016. "Statistical inference for familial disease models assuming exchangeability," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 220-225.
    • Handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:220-225
    DOI: 10.1016/j.spl.2016.08.006
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    References listed on IDEAS

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    1. Chang Yu & Daniel Zelterman, 2002. "Statistical Inference for Familial Disease Clusters," Biometrics, The International Biometric Society, vol. 58(3), pages 481-491, September.
    2. Catalina Stefanescu & Bruce W. Turnbull, 2003. "Likelihood Inference for Exchangeable Binary Data with Varying Cluster Sizes," Biometrics, The International Biometric Society, vol. 59(1), pages 18-24, March.
    3. Yu, Chang & Zelterman, Daniel, 2008. "Sums of exchangeable Bernoulli random variables for family and litter frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1636-1649, January.
    4. E. Olusegun George & Kyeongmi Cheon & Yilian Yuan & Aniko Szabo, 2016. "On exchangeable multinomial distributions," Biometrika, Biometrika Trust, vol. 103(2), pages 397-408.
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