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Blocking, efficiency and weighted optimality


  • Xiaowei Wang
  • J. P. Morgan


Optimal blocking is explored for experiments, such as those incorporating one or more controls, where not all treatment comparisons are of equal interest. Weighted optimality functions are employed in gaining both analytic and enumerative results; a catalogue of smaller optimal designs is provided. It is shown how design selection based on functions of variances, and on functions of efficiency factors, are both subsumed by the weighted approach. Copyright 2011, Oxford University Press.

Suggested Citation

  • Xiaowei Wang & J. P. Morgan, 2011. "Blocking, efficiency and weighted optimality," Biometrika, Biometrika Trust, vol. 98(4), pages 967-978.
  • Handle: RePEc:oup:biomet:v:98:y:2011:i:4:p:967-978

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    References listed on IDEAS

    1. Kai-tai Fang & Rahul Mukerjee, 2005. "Expected lengths of confidence intervals based on empirical discrepancy statistics," Biometrika, Biometrika Trust, vol. 92(2), pages 499-503, June.
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    5. T. J. Sweeting, 1999. "On the construction of Bayes-confidence regions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 849-861.
    6. Francesco Bravo, 2003. "Second-order power comparisons for a class of nonparametric likelihood-based tests," Biometrika, Biometrika Trust, vol. 90(4), pages 881-890, December.
    7. Susanne M. Schennach, 2005. "Bayesian exponentially tilted empirical likelihood," Biometrika, Biometrika Trust, vol. 92(1), pages 31-46, March.
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