Test statistics for association between markers on autosomal chromosomes and a disease have been extensively studied. No research has been reported on performance of such test statistics for association on the X chromosome. With 100,000 or more single-nucleotide polymorphisms (SNPs) available for genome-wide association studies, thousands of them come from the X chromosome. The X chromosome contains rich information about population history and linkage disequilibrium. To identify X-linked marker susceptibility to a disease, it is important to study properties of various statistics that can be used to test for association on the X chromosome. In this article, we compare performance of several approaches for testing association on the X chromosome, and examine how departure from Hardy-Weinberg equilibrium would affect type I error and power of these association tests using X-linked SNPs. The results are applied to the X chromosome of Klein et al. [2005], a genome-wide association study with 100K SNPs for age-related macular degeneration. We found that a SNP (rs10521496) covered by DIAPH2, known to cause premature ovarian failure (POF) in females, is associated with age-related macular degeneration.