bfpwr (version 0.1.6)

powerbf01: Power and sample size calculations for z-test Bayes factor

Description

Compute probability that z-test Bayes factor is smaller than a specified threshold (the power), or determine sample size to obtain a target power.

Usage

powerbf01(
  n = NULL,
  power = NULL,
  k = 1/10,
  sd = 1,
  null = 0,
  pm,
  psd,
  type = c("two.sample", "one.sample", "paired"),
  dpm = pm,
  dpsd = psd,
  nrange = c(1, 10^5)
)

Value

Object of class "power.bftest", a list of the arguments (including the computed one) augmented with method and note

elements

Arguments

n

Sample size (per group for two-sample tests). Has to be NULL if power is specified. Defaults to NULL

power

Target power. Has to be NULL if n is specified. Defaults to NULL

k

Bayes factor threshold. Defaults to 1/10, Jeffreys' threshold for 'strong evidence' against the null hypothesis

sd

Standard deviation of one observation (for type = "two.sample" or type = "one.sample") or of one difference within a pair of observations (type = "paired"). Is assumed to be known. Defaults to 1

null

Mean difference under the point null hypothesis. Defaults to 0

pm

Mean of the normal prior assigned to the mean difference under the alternative in the analysis

psd

Standard deviation of the normal prior assigned to the mean difference under the alternative in the analysis. Set to 0 to obtain a point prior at the prior mean

type

The type of test. One of "two.sample", "one.sample", "paired". Defaults to "two.sample"

dpm

Mean of the normal design prior assigned to the mean difference. Defaults to the same value as the analysis prior pm

dpsd

Standard deviation of the normal design prior assigned to the mean difference. Defaults to the same value as the analysis prior psd

nrange

Sample size search range over which numerical search is performed (only taken into account when n is NULL). Defaults to c(1, 10^5)

Author

Samuel Pawel

Details

This function provides a similar interface as stats::power.t.test. It also assumes that the data are continuous and that the parameter of interest is either a mean or a (standardized) mean difference. For some users, the low-level functions nbf01 (to directly compute the sample size for a fixed power) and pbf01 (to directly compute the power for a fixed sample size) may also be useful because they can be used for other data and parameter types.

See Also

plot.power.bftest, nbf01, pbf01, bf01

Examples

## determine power
powerbf01(n = 100, pm = 0, psd = 1, dpm = 0.5, dpsd = 0)

## determine sample size
powerbf01(power = 0.99, pm = 0, psd = 1, dpm = 0.5, dpsd = 0)