Accurate power approximations for chi2-tests in case-control association studies of complex disease genes

Abstract

A popular method for the analysis of case-control association studies is to compare the frequencies of the alleles between cases and controls by means of Pearson's chi2-statistic. Here, an approach for computing the power of this test is presented, which by computer simulation is shown to be more reliable than a previously published power approximation. Since the test based on Pearson's chi2- statistic can be anti-conservative if there is an excess of homozygotes for the susceptibility allele in the general population, it has been proposed to analyze case-control association studies by means of a trend test based on genotypes instead of alleles. We present an accurate power approximation for the trend test. The power approximations are implemented in an available computer program 'GenOdyPower', which in addition has an option to determine the empirical power of these tests by simulations.