A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

Newcombe, Paul J; Reck, Brian H; Sun, Jielin; Platek, Greg T; Verzilli, Claudio; Kader, A Karim; Kim, Seong-Tae; Hsu, Fang-Chi; Zhang, Zheng; Zheng, S Lilly; Mooser, Vincent E; Condreay, Lynn D; Spraggs, Colin F; Whittaker, John C; Rittmaster, Roger S; Xu, Jianfeng

Newcombe, Paul J; Reck, Brian H; Sun, Jielin; Platek, Greg T; Verzilli, Claudio; Kader, A Karim; Kim, Seong-Tae; Hsu, Fang-Chi; Zhang, Zheng; Zheng, S Lilly; Mooser, Vincent E; Condreay, Lynn D; Spraggs, Colin F; Whittaker, John C; Rittmaster, Roger S; Xu, Jianfeng.

Affiliation

Newcombe PJ; Genetics Division, GlaxoSmithKline, Stevenage, United Kingdom. paul.j.newcombe@gsk.com

Genet Epidemiol ; 36(1): 71-83, 2012 Jan.

Article in En | MEDLINE | ID: mdl-22890972

Subject(s)

Bayes Theorem; Genetic Predisposition to Disease; Logistic Models; Prostatic Neoplasms/genetics; Aged; Algorithms; Area Under Curve; Calibration; Genome-Wide Association Study; Humans; Male; Middle Aged; Models, Genetic; Models, Statistical; Polymorphism, Single Nucleotide; ROC Curve; Randomized Controlled Trials as Topic; White People/genetics

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Full text: 1 Database: MEDLINE Main subject: Prostatic Neoplasms / Logistic Models / Bayes Theorem / Genetic Predisposition to Disease Type of study: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limits: Aged / Humans / Male / Middle aged Language: En Year: 2012 Type: Article

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