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