num.trt <- 4 num.rep <- 60 tau.1 <- c(-2.5,0,0,2.5) tau.2 <- c(-5,0,0,5) tau.3 <- c(-10,0,0,10) sigma <- 16 df.trt <- num.trt-1 df.err <- num.trt*(num.rep-1) nc.0 <- 0 (nc.1 <- num.rep*sum((tau.1-mean(tau.1))^2)/(sigma^2)) (nc.2 <- num.rep*sum((tau.2-mean(tau.2))^2)/(sigma^2)) (nc.3 <- num.rep*sum((tau.3-mean(tau.3))^2)/(sigma^2)) y <- seq(0,15,.01) fy.0 <- df(y,df.trt,df.err,nc.0) fy.1 <- df(y,df.trt,df.err,nc.1) fy.2 <- df(y,df.trt,df.err,nc.2) fy.3 <- df(y,df.trt,df.err,nc.3) (f.crit <- qf(.95,df.trt,df.err)) plot(y,fy.0,type="l",main="Central and Non-central F-distributions") lines(y,fy.1,type="l",lty=2) lines(y,fy.2,type="l",lty=3) lines(y,fy.3,type="l",lty=4) abline(v=f.crit) legend(locator(1),c("F(nc.0)","F(nc.1)","F(nc.2)","F(nc.3)"),lty=1:4) (power.0 <- 1-pf(f.crit,df.trt,df.err,nc.0)) (power.1 <- 1-pf(f.crit,df.trt,df.err,nc.1)) (power.2 <- 1-pf(f.crit,df.trt,df.err,nc.2)) (power.3 <- 1-pf(f.crit,df.trt,df.err,nc.3))