Exact nonparametric meta-analysis for multiple independent doubly Type-II censored samples

William Volterman, N. Balakrishnan, Erhard Cramer

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Nonparametric inferential methods are discussed for the situation of multiple independent doubly Type-II censored samples. The basic distribution theory for the pooled sample is given assuming that the underlying distribution is continuous and it is demonstrated how the weights in the mixture representations of the pooled order statistics as a mixture of the usual order statistics can be obtained. This is used to construct nonparametric prediction intervals, tolerance intervals for a future sample, and confidence intervals for a population quantile. A small simulation study compares the exact coverage probabilities for population quantiles, to those obtained where the mixture weights are generated by simulation.

Original languageEnglish (US)
Pages (from-to)1243-1255
Number of pages13
JournalComputational Statistics and Data Analysis
Issue number5
StatePublished - May 1 2012
Externally publishedYes


  • Doubly Type-II censored sample
  • Meta-analysis
  • Mixtures
  • Nonparametric confidence intervals
  • Nonparametric prediction intervals
  • Nonparametric tolerance intervals
  • Pooled sample

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics


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