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Multistage designs in the genomic era: Providing balance in complex disease studies
Author(s) -
Dubé MariePierre,
Schmidt Silke,
Hauser Elizabeth
Publication year - 2007
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20288
Subject(s) - replication (statistics) , computer science , range (aeronautics) , computational complexity theory , statistics , mathematics , algorithm , engineering , aerospace engineering
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.