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Journal articles
Multistage designs in the genomic era: providing balance in complex disease studies.
Marie-Pierre Dubé
1
Silke Schmidt
2
Elizabeth Hauser
2, *
Hatef Darabi
Jing Li
Amina Barhdadi
Xuexia Wang
Quiying Sha
Zhaogong Zhang
Tao Wang
Hugues Aschard
3
Mickael Guedj
Rori Rohlfs
Amy Anderson
Chelsea Taylor
Lucia Mirea
Radoslav Nickolov
Valentin Milanov
Hsin-Chao Yang
Yeunjoo Song
Ritwik Sinha
Marie-Pierre Dubé 1
Author
Silke Schmidt 2
Author
Elizabeth Hauser 2
Correspondent author
Hatef Darabi
Author
Ritwik Sinha
Author
1
Department of Statistical Genetics (Montreal, Quebec and Department of Medicine, , 2900, Edouard-Montpetit Blvd., Montreal, Quebec H3T 1J4 - Canada)
- UdeM - Université de Montréal (2900 Boulevard Edouard-Montpetit, Montréal, QC H3T 1J4 - Canada)
- Research Centre of the Montreal Heart Institute (France)
2
Department of Medicine (Durham, North Carolina - United States)
- Center for Human Genetics (France)
- Duke University Medical Center (2301 Erwin Rd, Durham, NC 27710 - United States)
3
Méthodologie statistique et épidémiologie génétique de maladies multifactorielles (Tour Evry 2 - 2 ème étage 523 Place des Terrasses de l'Agora 91034 Evry - France)
- UEVE - Université d'Évry-Val-d'Essonne (Boulevard François Mitterrand 91025 Evry Cedex - France)
- INSERM - Institut National de la Santé et de la Recherche Médicale : U794 (101, rue de Tolbiac, 75013 Paris - France)
Abstract : In this summary paper, we describe the contributions included in the Multistage Design group (Group 14) at the Genetic Analysis Workshop 15, which was held during November 12-14, 2006. Our group contrasted and compared different approaches to reducing complexity in a genetic study through implementation of staged designs. Most groups used the simulated dataset (problem 3), which provided ample opportunities for evaluating various staged designs. A wide range of multistage designs that targeted different aspects of complexity were explored. We categorized these approaches as reducing phenotypic complexity, model complexity, analytic complexity or genetic complexity. In general we learned that: (1) when staged designs are carefully planned and implemented, the power loss compared to a single-stage analysis can be minimized and study cost is greatly reduced; (2) a joint analysis of the results from each stage is generally more powerful than treating the second stage as a replication analysis.
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https://www.hal.inserm.fr/inserm-00399067
Contributor : Aschard Hugues <>
Submitted on : Thursday, June 25, 2009 - 3:48:12 PM
Last modification on : Tuesday, September 1, 2020 - 4:24:01 PM
Contributor : Aschard Hugues <>
Submitted on : Thursday, June 25, 2009 - 3:48:12 PM
Last modification on : Tuesday, September 1, 2020 - 4:24:01 PM
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- HAL Id : inserm-00399067, version 1
- DOI : 10.1002/gepi.20288
- PUBMED : 18046769
Citation
Marie-Pierre Dubé, Silke Schmidt, Elizabeth Hauser, Hatef Darabi, Jing Li, et al.. Multistage designs in the genomic era: providing balance in complex disease studies.. Genetic Epidemiology, Wiley, 2007, 31 Suppl 1, pp.S118-23. ⟨10.1002/gepi.20288⟩. ⟨inserm-00399067⟩
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