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Statistical Methods and Applications

, Volume 11, Issue 2, pp 161–173 | Cite as

Extending permutation conditional inference to unconditional ones

  • Fortunato Pesarin
Statistical Methods

Abstract

In this presentation we discuss the extension of permutation conditional inferences to unconditional or population ones. Within the parametric approach this extension is possible when the data set is randomly selected by well-designed sampling procedures on well-defined population distributions, provided that their nuisance parameters have boundely complete statistics in the null hypothesis or are provided with invariant statistics. When these conditions fail, especially if selection-bias procedures are used for data collection processes, in general most of the parametric inferential extensions are wrong or misleading. We will see that, since they are provided with similarity and conditional unbiasedness properties and if correctly applicable, permutation tests may extend, at least in a weak sense, conditional to unconditional inferences.

Key words

Conditional inference exchangeability permutation tests similarity unconditional inference 

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Copyright information

© Springer-Verlag 2002

Authors and Affiliations

  • Fortunato Pesarin
    • 1
  1. 1.Dipartimento di Scienze StatistichePADOVAItaly

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