MASS anorexia data: Analysis and power simulation

  1. Analyze the original data:
    • In R, see ?MASS::anorexia
    • Estimate the average treatment effect (ATE) for FT relative to CBT.
    • What is the 95% CI for the ATE?
    • What are the pre- and post-weight means for the two groups?
    • What are the baseline-adjusted means for the two groups?
## Data preparation
data(anorexia, package = "MASS")
dat <-
  subset(anorexia, Treat != "Cont") |>  # exclude control group
  droplevels()                          # drop empty factor levels
lbs2kg <- 0.4535924
dat$Prewt  <- lbs2kg * dat$Prewt        # to kg
dat$Postwt <- lbs2kg * dat$Postwt
lattice::xyplot(Postwt ~ Prewt, dat, groups = Treat,
                type = c("g", "r", "p"), auto.key = TRUE)

  1. Run a power simulation for a replication study:
    • Draw plausible pre-weights.
    • Specify the minimum relevant effect.
    • Set the remaining parameters to plausible values.
    • What is the sample size required for the test to detect the effect with 80% power?
    • How robust is the power simulation when you repeat it with a new set of pre-weights? Try it!
    • Recover the parameters of the ANCOVA model.
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