Contaminated normal modeling with application to microarray data analysis

Hongying Dai, Richard Charnigo

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


A contaminated beta model (1 - γ)B(1, 1) + γB(α, β) is often used to describe the distribution of P-values arising from a microarray experiment. The authors propose and examine a different approach: namely, using a contaminated normal model (1 - γ)N(0, σ2) + γN(μ, σ2) to describe the distribution of Z statistics or suitably transformed T statistics. The authors then address whether a researcher who has Z statistics should analyze them using the contaminated normal model or whether the Z statistics should be converted to P-values to be analyzed using the contaminated beta model. The authors also provide a decisiontheoretic perspective on the analysis of Z statistics.

Original languageEnglish
Pages (from-to)315-332
Number of pages18
JournalCanadian Journal of Statistics
Issue number3
StatePublished - Sep 2010


  • Contaminated beta model
  • Contaminated normal model
  • D-test
  • MLRT
  • Maximum modified likelihood
  • Microarray
  • Mixture model
  • Omnibus test

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Contaminated normal modeling with application to microarray data analysis'. Together they form a unique fingerprint.

Cite this