A Bootstrap Approach to Estimating Power for Linkage Heterogeneity
S.M. Leal, J.Ott
Genetic Epidemiology , 10(6), 465-70 (1993)
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.
