Abstract
Objective: In past years, the focus of genetic-epidemiological studies has shifted to analyzing complex diseases. Here, single genes often contribute only little to the manifestation of traits so that many probands have to be included in a study to reliably detect small effects. To reduce the number of required phenotypings and genotypings and thus facilitate analyzing complex traits, sequential study designs can be applied. Methods: For sequential analyses of complex diseases in association studies, we compare the procedure by Sobell et al. (Am J Med Genet 1993;48:28-35) with the adaptation of formal group sequential study designs by Pampallona and Tsiatis (J Stat Plan Inf 1994;42:19-35). Error rates and average sample sizes are investigated by Monte-Carlo simulations. Results: Formal sequential designs have a higher power regardless of underlying genetic effects. In addition, compared with conventional designs with fixed samples, average sample sizes are reduced considerably; under the null hypothesis of no association, up to 50% of the required sample size can be spared. Conclusions: To increase the efficiency of genetic-epidemiological case-control studies, we recommend using formal group sequential study designs. The tremendous savings in average sample sizes are expected to affect both cost and time spent on large-scale studies.
| Original language | English |
|---|---|
| Journal | Human Heredity |
| Volume | 56 |
| Issue number | 1-3 |
| Pages (from-to) | 63-72 |
| Number of pages | 10 |
| ISSN | 0001-5652 |
| DOIs | |
| Publication status | Published - 2003 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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