| fixedHajnal.onez_es {NAP} | R Documentation |
Fixed-design one-sample z-tests using Hajnal's ratio for varied sample sizes
Description
In two-sided fixed design one-sample z-tests with composite alternative prior assumed on the standardized effect size \mu/\sigma_0 under the alternative, this function calculates the expected log(Hajnal's ratio) at a prefixed standardized effect size for a varied range of sample sizes.
Usage
fixedHajnal.onez_es(es = 0, es1 = 0.3, nmin = 20, nmax = 5000,
sigma0 = 1, batch.size.increment, nReplicate = 50000)
Arguments
es |
Numeric. Standardized effect size where the expected weights of evidence is desired. Default: |
es1 |
Positive numeric. Default: |
nmin |
Positive integer. Minimum sample size to be considered. Default: 20. |
nmax |
Positive integer. Maximum sample size to be considered. Default: 5000. |
sigma0 |
Positive numeric. Known standard deviation in the population. Default: 1. |
batch.size.increment |
function. Increment in sample size. The sequence of sample size thus considered for the fixed design test is from |
nReplicate |
Positve integer. Number of replicated studies based on which the expected weights of evidence is calculated. Default: 50,000. |
Value
A list with two components named summary and BF.
$summary is a data frame with columns n containing the values of sample sizes and avg.logBF containing the expected log(Hajnal's ratios) at those values.
$BF is a matrix of dimension number of sample sizes considered by nReplicate. Each row contains the Hajnal's ratios at the corresponding sample size in nReplicate replicated studies.
Author(s)
Sandipan Pramanik and Valen E. Johnson
References
Hajnal, J. (1961). A two-sample sequential t-test.Biometrika, 48:65-75, [Article].
Schnuerch, M. and Erdfelder, E. (2020). A two-sample sequential t-test.Biometrika, 48:65-75, [Article].
Examples
out = fixedHajnal.onez_es(nmax = 100)