simER {ESTER}

Simulates sequential testing with evidence ratios

Description

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.

Usage

simER(cohensd = 0, nmin = 20, nmax = 100, boundary = 10, nsims = 20,
  ic = bic, cores = 2, verbose = FALSE)

Arguments

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

Value

An object of class data.frame, which contains...

Author(s)

Ladislas Nalborczyk <[e-mail]>

See Also

ictab, analysER

Examples

## 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)