期刊
EUROPEAN JOURNAL OF EPIDEMIOLOGY
卷 24, 期 12, 页码 737-741出版社
SPRINGER
DOI: 10.1007/s10654-009-9393-0
关键词
Bayesian analysis; Effect (odds ratio); Genome-wide association study; Single nucleotide polymorphism; Statistics
资金
- The Swedish Council for Working Life and Social Research
- Swedish Cancer Fund
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.
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