Original Article

Multistage designs in the genomic era: Providing balance in complex disease studies

  1. Marie-Pierre Dubé1,
  2. Silke Schmidt2,
  3. Elizabeth Hauser2,*

Article first published online: 28 NOV 2007

DOI: 10.1002/gepi.20288

Issue

Genetic Epidemiology

Genetic Epidemiology

Supplement: Genetic Analysis Workshop 15: Summaries of the Design and Analysis of Genomic Data

Volume 31, Issue S1, pages S118–S123, 2007

Additional Information

How to Cite

Dubé, M.-P., Schmidt, S. and Hauser, E. (2007), Multistage designs in the genomic era: Providing balance in complex disease studies. Genet. Epidemiol., 31: S118–S123. doi: 10.1002/gepi.20288

Author Information

  1. 1

    Research Centre of the Montreal Heart Institute, Department of Statistical Genetics, Montreal, Quebec and Department of Medicine, Université de Montréal, 2900, Edouard-Montpetit Blvd., Montreal, Quebec H3T 1J4, Canada

  2. 2

    Center for Human Genetics, Department of Medicine, Duke University Medical Center, Durham, North Carolina

*Center for Human Genetics, Duke University Medical Center, DUMC Box 3445, Durham, NC 27710, USA

  1. A complete list of Group 14 primary contributing authors is given in the Acknowledgment section.

Publication History

  1. Issue published online: 28 NOV 2007
  2. Article first published online: 28 NOV 2007

Funded by

  • NIH. Grant Numbers: MH59528, EY015216
  • Neurosciences Education and Research Foundation
  • Fonds de la recherche en santé du Québec

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Keywords:

  • two-stage study design;
  • replication;
  • joint analysis;
  • statistical power;
  • genetic association

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. Genet. Epidemiol. 31 (Suppl. 1):S118–S123, 2007. © 2007 Wiley-Liss, Inc.

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