Hardy-Weinberg testing for continuous data.

Estimation of allelic and genotypic distributions for continuous data using kernel density estimation is discussed and illustrated for some variable number of tandem repeat data. These kernel density estimates provide a useful representation of data when only some of the many variants at a locus are present in a sample. Two Hardy-Weinberg test procedures are introduced for continuous data: a continuous chi-square test with test statistic T(CCS) and a test based on Hellinger's distance with test statistic T(HD). Simulations are used to compare the powers of these tests to each other and to the powers of a test of intraclass correlation T(IC), as well as to the power of Fisher's exact test T(FET) applied to discretized data. Results indicate that the power of T(CCS) is better than that of T(HD), but neither is as powerful as T(FET). The intraclass correlation test does not perform as well as the other tests examined in this article.