Power with Fieller [General Sta­tis­tics]

posted by martin  – Austria, 2012-11-15 18:29 (4961 d 20:35 ago) – Posting: # 9534
Views: 7,351

Dear all!

We recently encountered an unexpected behavior (at least I was not aware of it) with Fieller confidence intervals. It seems that the power for showing equivalence is not maximized at delta = 1 for rather large variances. Is there an error in the code or is this behavior well known?

best regards

martin

library(pairwiseCI)
set.seed(7750)
nsim <- 1E5
sd <- 0.25
res1 <- res2 <- res3 <- res4 <- matrix(NA,ncol=2,nrow=nsim)
n <- 10
for(i in 1:nsim){
   a1 <- rnorm(n,1,sd=sd)
   a2 <- rnorm(n,0.975,sd=sd)
   a3 <- rnorm(n,1.025,sd=sd)
   a4 <- rnorm(n,1.050,sd=sd)
   b <- rnorm(n,1,sd=sd)
   res1[i,] <- as.vector(Param.ratio(a1,b,conf.level=0.9,var.equal=F)$conf.int)
   res2[i,] <- as.vector(Param.ratio(a2,b,conf.level=0.9,var.equal=F)$conf.int)
   res3[i,] <- as.vector(Param.ratio(a3,b,conf.level=0.9,var.equal=F)$conf.int)
   res4[i,] <- as.vector(Param.ratio(a4,b,conf.level=0.9,var.equal=F)$conf.int)
}

# delta=1: expected to have the largest power
mean(res1[,1]>0.8 & res1[,2]<1.25)
# delta=0.975
mean(res2[,1]>0.8 & res2[,2]<1.25)
# delta=1.025
mean(res3[,1]>0.8 & res3[,2]<1.25)
# delta=1.05
mean(res4[,1]>0.8 & res4[,2]<1.25)

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