title: A bootstrap approach to estimating power for linkage heterogeneity.
abstract: We examined the power of detecting linkage heterogeneity when the null hypothesis is that all families are linked to one locus (A) and the two alternative hypotheses are either 1) a proportion of the families are linked to locus A and the remaining families are linked to a second locus B or 2) a proportion of the families are linked to locus A or B and a third proportion of the families are unlinked to either locus. The power of detecting linkage heterogeneity is estimated for various proportions of families linked to loci A, B or unlinked to either locus (sampling under the alternative hypothesis). To estimate the significance level, the data set is sampled under the null hypothesis. For sampling under both hypotheses, a bootstrap approach is employed, sampling the simulated pedigrees with replacement. The power to detect linkage heterogeneity is strongest when the recombination fraction is 0 and equal proportions of the families are linked to loci A and B. The power decreases as the recombination fraction increases, the proportion of unlinked families increases and the disparity between the proportion of the families linked to either locus A or B increases. In the data set of 32 Duke Familial Alzheimer Disease families, when equal proportions of families are linked to loci A and B, the power to detect linkage heterogeneity is 0.94 using a likelihood ratio criterion of 10:1. The p value that corresponds to the likelihood ratio of 10:1 is estimated as 0.013 with a 95% confidence interval for p ranging from 0.012 to 0.014.
authors.affiliation: Department of Psychiatry, Columbia University, New York, New York 10032.
authors.forename: S M
authors.initials: SM
authors.lastname: Leal
authors.forename: J
authors.initials: J
authors.lastname: Ott
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000453:epidemiology / Q000235:genetics; D008040:Genetic Linkage; D014644:Genetic Variation; D006801:Humans; D009657:North Carolina / Q000453:epidemiology; D013223:Statistics as Topic / Q000379:methods