Optimum study designs.
Because simplistic designs will lead to prohibitively large sample sizes, the optimization of genetic study designs is critical for successfully mapping genes for complex diseases. Creative designs are necessary for detecting and amplifying the usually weak signals for complex traits. Two important outcomes of a study design--power and resolution--are implicitly tied together by the principle of uncertainty. Overemphasis on either one may lead to suboptimal designs. To achieve optimality for a particular study, therefore, practical measures such as cost-effectiveness must be used to strike a balance between power and resolution. In this light, the myriad of factors involved in study design can be checked for their effects on the ultimate outcomes, and the popular existing designs can be sorted into building blocks that may be useful for particular situations. It is hoped that imaginative construction of novel designs using such building blocks will lead to enhanced efficiency in finding genes for complex human traits.
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Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
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D016022:Case-Control Studies; D002874:Chromosome Mapping / Q000191:economics / Q000379:methods*; D003362:Cost-Benefit Analysis; D003710:Demography; D008040:Genetic Linkage; D005838:Genotype; D006801:Humans; D015201:Meta-Analysis as Topic; D010641:Phenotype; D018401:Sample Size