simER {ESTER} | R Documentation |
Simulates one or many sequential testing with evidence ratios from independent two-groups comparisons, as a function of sample size and standardized mean difference. Evidence ratios are computed from the so-called Akaike weights from either the Akaike Information Criterion or the Bayesian Information Criterion.
simER(cohensd = 0, nmin = 20, nmax = 100, boundary = 10, nsims = 20,
ic = bic, cores = 2, verbose = FALSE)
cohensd |
Expected effect size |
nmin |
Minimum sample size from which start computing ERs |
nmax |
Maximum sample size at which stop computing ERs |
boundary |
The Evidence Ratio (or its reciprocal) at which the run is stopped as well |
nsims |
Number of simulated samples (should be dividable by cores) |
ic |
Indicates whether to use the aic or the bic |
cores |
Number of parallel processes. If cores is set to 1, no parallel framework is used (default is two cores). |
verbose |
Show output about progress |
An object of class data.frame
, which contains...
Ladislas Nalborczyk <ladislas.nalborczyk@gmail.com>
## Not run:
sim <- simER(cohensd = 0.8, nmin = 20, nmax = 100, boundary = 10,
nsims = 100, ic = bic, cores = 2, verbose = TRUE)
plot(sim, log = TRUE, hist = TRUE)
## End(Not run)