powerCurve: Estimate power at a range of sample sizes.

In simr: Power Analysis for Generalised Linear Mixed Models by Simulation

Estimate power at a range of sample sizes.

Description

This function runs powerSim over a range of sample sizes.

Usage

powerCurve(
  fit,
  test = fixed(getDefaultXname(fit)),
  sim = fit,
  along = getDefaultXname(fit),
  within,
  breaks,
  seed,
  fitOpts = list(),
  testOpts = list(),
  simOpts = list(),
  ...
)

Arguments

fit	a fitted model object (see doFit).
test	specify the test to perform. By default, the first fixed effect in fit will be tested. (see: tests).
sim	an object to simulate from. By default this is the same as fit (see doSim).
along	the name of an explanatory variable. This variable will have its number of levels varied.
within	names of grouping variables, separated by "+" or ",". Each combination of groups will be extended to n rows.
breaks	number of levels of the variable specified by along at each point on the power curve.
seed	specify a random number generator seed, for reproducible results.
fitOpts	extra arguments for doFit.
testOpts	extra arguments for doTest.
simOpts	extra arguments for doSim.
...	any additional arguments are passed on to simrOptions. Common options include: nsim: the number of simulations to run (default is 1000). alpha: the significance level for the statistical test (default is 0.05). progress: use progress bars during calculations (default is TRUE).

See Also

print.powerCurve, summary.powerCurve, confint.powerCurve

Examples

## Not run: 
fm <- lmer(y ~ x + (1|g), data=simdata)
pc1 <- powerCurve(fm)
pc2 <- powerCurve(fm, breaks=c(4,6,8,10))
print(pc2)
plot(pc2)

## End(Not run)

simr documentation built on April 14, 2023, 12:24 a.m.