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An approximately optimal non-parametric procedure for analyzing exchangeable binary data with random cluster sizes

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  • Hui-Xiu Zhao
  • Jin-Guan Lin

Abstract

For the exchangeable binary data with random cluster sizes, we develop an approximately optimal non-parametric procedure for obtaining estimates of the moments of all orders. Moreover, based on this procedure, we can also obtain efficient estimates of underlying parameters of moments of all orders. An application is made to data sets from a developmental toxicity study. Simulation results show that our procedure is valid and performs better than Bowman and George’s procedure and the pairwise likelihood procedure. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Hui-Xiu Zhao & Jin-Guan Lin, 2013. "An approximately optimal non-parametric procedure for analyzing exchangeable binary data with random cluster sizes," Computational Statistics, Springer, vol. 28(5), pages 2029-2047, October.
    • Handle: RePEc:spr:compst:v:28:y:2013:i:5:p:2029-2047
    DOI: 10.1007/s00180-012-0393-2
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    References listed on IDEAS

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    1. Kuk, Anthony Y. C. & Nott, David J., 2000. "A pairwise likelihood approach to analyzing correlated binary data," Statistics & Probability Letters, Elsevier, vol. 47(4), pages 329-335, May.
    2. Anthony Y. C. Kuk, 2004. "A litter‐based approach to risk assessment in developmental toxicity studies via a power family of completely monotone functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(2), pages 369-386, April.
    3. 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.
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