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.
fixedHajnal.onez_es(es = 0, es1 = 0.3, nmin = 20, nmax = 5000,
sigma0 = 1, batch.size.increment, nReplicate = 50000)
Numeric. Standardized effect size where the expected weights of evidence is desired. Default: 0
.
Positive numeric. Default: \(0.3\). For this, the composite alternative prior on the standardized effect size \(\mu/\sigma_0\) takes values \(0.3\) and \(-0.3\) each with equal probability 1/2.
Positive integer. Minimum sample size to be considered. Default: 20.
Positive integer. Maximum sample size to be considered. Default: 5000.
Positive numeric. Known standard deviation in the population. Default: 1.
function. Increment in sample size. The sequence of sample size thus considered for the fixed design test is from nmin
to nmax
with an increment of batch.size.increment
. Default: function(narg){20}
. This means an increment of 20 samples at each step.
Positve integer. Number of replicated studies based on which the expected weights of evidence is calculated. Default: 50,000.
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.
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].
# NOT RUN {
out = fixedHajnal.onez_es(nmax = 100)
# }
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