Multistage designs in the genomic era: providing balance in complex disease studies.
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.
Research Centre of the Montreal Heart Institute, Department of Statistical Genetics, Montreal, Quebec, Canada.
Marie-Pierre
MP
Dubé
Silke
S
Schmidt
Elizabeth
E
Hauser
Hatef
H
Darabi
Jing
J
Li
Amina
A
Barhdadi
Xuexia
X
Wang
Quiying
Q
Sha
Zhaogong
Z
Zhang
Tao
T
Wang
Hugues
H
Aschard
Mickael
M
Guedj
Rori
R
Rohlfs
Amy
A
Anderson
Chelsea
C
Taylor
Lucia
L
Mirea
Radoslav
R
Nickolov
Valentin
V
Milanov
Hsin-Chao
HC
Yang
Yeunjoo
Y
Song
Ritwik
R
Sinha
D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D012107:Research Design