Statistical inference based on pooled data: A moment-based estimating equation approach

Howard D. Bondell, Aiyi Liu, Enrique F. Schisterman

Research output: Contribution to journalArticlepeer-review

Abstract

We consider statistical inference on parameters of a distribution when only pooled data are observed. A moment-based estimating equation approach is proposed to deal with situations where likelihood functions based on pooled data are difficult to work with. We outline the method to obtain estimates and test statistics of the parameters of interest in the general setting. We demonstrate the approach on the family of distributions generated by the Box-Cox transformation model, and, in the process, construct tests for goodness of fit based on the pooled data.

Original languageEnglish (US)
Pages (from-to)129-140
Number of pages12
JournalJournal of Applied Statistics
Volume34
Issue number2
DOIs
StatePublished - Mar 2007
Externally publishedYes

Keywords

  • Box-Cox transformation
  • Goodness-of-fit
  • Lognormal distribution
  • Moments
  • Pooling biospecimens
  • Set-based observations

ASJC Scopus subject areas

  • Statistics and Probability

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