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- Title
HAPLOTYPE-BASED STATISTICAL INFERENCE FOR POPULATION-BASED CASE-CONTROL AND CROSS-SECTIONAL STUDIES WITH COMPLEX SAMPLE DESIGNS.
- Authors
DAOYING LIN; LINGXIAO WANG; YAN LI
- Abstract
In recent years, the use of complex sampling (e.g., stratified multistage cluster sampling) has become more common in population-based case-control or cross-sectional studies for the selection of study subjects in genetic association studies. This has been prompted by the usual advantages of conducting complex sampling, such as time and cost efficiency. More important, proper complex sample designs can obtain representative samples from the target population and thus avoid the biased selection of controls and/or cases. However, two complications--differential population weights and intracluster correlation--are induced by the complex sampling. Although most single nucleotide polymorphism (SNP)-based association studies with complex sampling account for these two complications, many recent haplotype-based genetic association studies with complex sampling tend to ignore them in the estimation of haplotype frequencies, regression coefficients, or both, which can lead to invalid inferences. Therefore, there is a need to develop statistical methods for taking into account the complications induced by complex sampling in haplotype-based association studies with complex sample designs. In this paper, we propose methods that properly account for complex sample designs. Our methods are evaluated by simulation studies and illustrated using data from the U.S. Kidney Cancer Study and the Third National Health and Nutrition Examination Survey (NHANES III).
- Subjects
STATISTICAL methods in haplotypes; SINGLE nucleotide polymorphisms; CLUSTER sampling; STATISTICAL sampling; COST
- Publication
Journal of Survey Statistics & Methodology, 2016, Vol 4, Issue 2, p188
- ISSN
2325-0984
- Publication type
Article
- DOI
10.1093/jssam/smv040