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powerCurve

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

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

Power Analysis for Generalised Linear Mixed Models by Simulation

v1.0.5
GPL (>= 2)
Authors
Green Peter [aut, cre] (<https://orcid.org/0000-0002-0238-9852>), MacLeod Catriona [aut], Alday Phillip [ctb]
Initial release

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