Biostatistics Advance Access published online on September 10, 2009
Biostatistics, doi:10.1093/biostatistics/kxp035
Trend tests for genetic association using population-based cross-sectional complex survey data
Department of Statistics, The George Washington University, Washington, DC 20052, USA and The EMMES Corporation, 401 North Washington Street, Rockville, MD 20850, USA
Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA
Department of Statistics and Finance, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China and Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20852, USA
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
Department of Statistics, The George Washington University, Washington, DC 20052, USA and Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20852, USA zli{at}gwu.edu
* To whom correspondence should be addressed.
Genetic data collected from surveys such as the Third National Health and Nutrition Examination Survey (NHANES III) enable researchers to investigate the association between wide varieties of health factors and genetic variation for the US population. Tests for trend in disease with increasing number of alleles have been developed for simple random samples. However, surveys such as the NHANES III have complex sample designs involving multistage cluster sampling and sample weighting. These types of sample designs can affect Type I error and power properties of statistical tests based on simple random samples. In order to address these issues, we have derived tests of trend based on Wald and quasi-score statistics, with and without assuming a genetic model, that account for the complex sampling design. The finite-sample properties of the proposed test procedures are evaluated via Monte Carlo simulation studies. We make recommendations about the choice of the test statistic depending on whether or not the underlying genetic model is known. Proposed test statistics are applied to NHANES III data to test for associations between the locus ADRB2 (rs1042713) and obesity, between VDR (rs2239185) and high blood lead level, and between TGFB1 (rs1982073) and asthma.
Keywords: Complex sampling; F-version of Rao–Scott second-order correction; Quasi-score test; Survey data; Trend test
Received February 26, 2009; revised August 17, 2009; accepted for publication August 18, 2009.