num.trt <- 4 num.rep <- c(15, 30, 45, 60) tau <- c(-5,0,0,5) sigma <- 16 (df.trt <- num.trt-1) (df.err <- num.trt*(num.rep-1)) (nc.0 <- 0) (nc.1 <- num.rep*sum((tau-mean(tau))^2)/(sigma^2)) (f.crit <- qf(.95,df.trt,df.err)) y <- seq(0,10,.01) fy.0 <- df(y,df.trt,df.err[1],nc.0) fy.1 <- df(y,df.trt,df.err[1],nc.1[1]) par(mfrow=c(2,2)) plot(y,fy.0,type="l",main="Central/NC F-dists, num.reps=15") lines(y,fy.1,type="l",lty=2) abline(v=f.crit[1]) fy.0 <- df(y,df.trt,df.err[2],nc.0) fy.1 <- df(y,df.trt,df.err[2],nc.1[2]) plot(y,fy.0,type="l",main="Central/NC F-dists, num.reps=30") lines(y,fy.1,type="l",lty=2) abline(v=f.crit[2]) fy.0 <- df(y,df.trt,df.err[3],nc.0) fy.1 <- df(y,df.trt,df.err[3],nc.1[3]) plot(y,fy.0,type="l",main="Central/NC F-dists, num.reps=45") lines(y,fy.1,type="l",lty=2) abline(v=f.crit[3]) fy.0 <- df(y,df.trt,df.err[4],nc.0) fy.1 <- df(y,df.trt,df.err[4],nc.1[4]) plot(y,fy.0,type="l",main="Central/NC F-dists, num.reps=60") lines(y,fy.1,type="l",lty=2) abline(v=f.crit[4]) (power.1 <- 1-pf(f.crit[1],df.trt,df.err[1],nc.1[1])) (power.2 <- 1-pf(f.crit[2],df.trt,df.err[2],nc.1[2])) (power.3 <- 1-pf(f.crit[3],df.trt,df.err[3],nc.1[3])) (power.4 <- 1-pf(f.crit[4],df.trt,df.err[4],nc.1[4]))