MASS anorexia data: Analysis and power simulation
- 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)

- 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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