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

被引：13
|
作者：
Stromberg, Ulf [1 ,2 ]
机构：
[1] Univ Lund Hosp, Dept Occupat & Environm Med, S-22185 Lund, Sweden
[2] Lund Univ, Dept Occupat & Environm Med, Lund, Sweden
来源：
EUROPEAN JOURNAL OF EPIDEMIOLOGY | 2009年 / 24卷 / 12期
关键词：
Bayesian analysis; Effect (odds ratio); Genome-wide association study; Single nucleotide polymorphism; Statistics; GENOME-WIDE ASSOCIATION; WINNERS CURSE; BIAS; ODDS; PROBABILITY; SELECTION; MARKERS; SIGNALS; FALSE;
D O I：
10.1007/s10654-009-9393-0
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
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.
引用
收藏
页码：737 / 741
页数：5
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