In mapping diseases of complex aetiology, conventional linkage approaches narrow the location of the disease susceptibility locus to quite a large region so that candidate gene association studies are then necessary to further isolate these genes. However, even in the simplest scenario where the candidate locus is bi-allelic, two statistical tests with various correcting factors have been proposed: a chi-square 1 df test (counting chromosomes) which may be slightly conservative and a 2 df chi-square test (counting genotypes) which may lack power because of the extra degree of freedom. This paper introduces a better and more powerful alternative which turns out to be a compromise between the two existing statistical tests. The asymptotic distribution of this test statistic is determined and the efficacy of the 3 tests are compared under different genetic models by simulation.