The genetics Package

36 power.casectrlValuepopulation joint prob. (f.mod = 1 under Ho)Case p(D, genotype) = p(D|genotype) = f.mod*piControl p(D_not, genotype) = p(genotype)*(1 - p(D|genotype)) = fHW*(1-f.mod*pi)population conditional prob. (f.mod = 1 under Ho)Case p(genotype|D) = p(D , genotype)/P(D ) = P(D , genotype)/sumControl p(genotype|D_not) = p(D_not, genotype)/P(D_not) = P(D_not, genotype)/sumsample or allocation probability1:1 case-control design p(D|Sample) = fc = 1/21:2 case-control design fc = 1/3a prospective designfc = sum(fHW*f.mod*pi)sample joint prob. (f.mod = 1 under Ho)for prospective design, this is the same as population joint prob. since 'fc' canceCase p(genotype,D |sample) = p(genotype|D )* p(D|Sample) = fc *Control p(genotype,D_not|sample) = p(genotype|D_not)*(1 - p(D|Sample)) = (1-fc)*power for the specified parameter values.Author(s)Michael Man /emailMichael.Man@pfizer.comReferencesLong, A. D. and C. H. Langley (1997). Genetic analysis of complex traits. Science 275: 1328.Examples# single calcpower.casectrl(p=0.1, N=50, gamma=1.1, kp=.1, alpha=5e-2, minh='r')# for a range of sample sizespower.casectrl(p=0.1, N=c(25,50,100,200,500), gamma=1.1, kp=.1,alpha=5e-2, minh='r')# create a power tablefun