Empirical Bayes and semi-Bayes adjustments for a vast number of estimations.

Research output: Contribution to journalArticlepeer-review

Abstract

Investigators in modern molecular/genetic epidemiology studies commonly analyze data on a vast number of candidate genetic markers. In such situations, rather than conventional estimation of effects (odds ratios), more accurate estimation methods are needed. The author proposes consideration of empirical Bayes and semi-Bayes methods, which yield 'adjustments for multiple estimations' by shrinking conventional effect estimates towards the overall average effect.
Original languageEnglish
Pages (from-to)737-741
JournalEuropean Journal of Epidemiology
Volume24
DOIs
Publication statusPublished - 2009

Subject classification (UKÄ)

  • Public Health, Global Health, Social Medicine and Epidemiology

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