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Efficiently Simulating the Coverage Properties of Interval Estimates

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  • D. B. Rubin
  • N. Schenker

Abstract

Methods of simulating the frequency coverage of an interval estimate by simulating the average Bayesian posterior probability coverage are presented. The methods can be much more efficient than the standard method that simulates the hit rate of the interval. The possible increased efficiency is illustrated using three examples: estimating a binomial probability, bootstrapping a variance, and multiple imputation intervals for the mean.

Suggested Citation

  • D. B. Rubin & N. Schenker, 1986. "Efficiently Simulating the Coverage Properties of Interval Estimates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(2), pages 159-167, June.
    • Handle: RePEc:bla:jorssc:v:35:y:1986:i:2:p:159-167
    DOI: 10.2307/2347266
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    Cited by:

    1. James Stamey & Dean Young & Tom Bratcher, 2006. "Bayesian sample-size determination for one and two Poisson rate parameters with applications to quality control," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(6), pages 583-594.
    2. Dranove, David & Lindrooth, Richard & White, William D. & Zwanziger, Jack, 2008. "Is the impact of managed care on hospital prices decreasing?," Journal of Health Economics, Elsevier, vol. 27(2), pages 362-376, March.

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