Description Usage Arguments Value Author(s) References Examples
In two-sided fixed design one-sample z-tests with composite alternative prior assumed on the standardized effect size μ/σ_0 under the alternative and a prefixed sample size, this function calculates the expected log(Hajnal's ratio) at a varied range of standardized effect sizes.
1 2 3 | fixedHajnal.onez_n(es1 = 0.3, es = c(0, 0.2, 0.3, 0.5),
n.fixed = 20, sigma0 = 1,
nReplicate = 50000, nCore)
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es1 |
Positive numeric. Default: 0.3. For this, the composite alternative prior on the standardized effect size μ/σ_0 takes values 0.3 and -0.3 each with equal probability 1/2. |
es |
Numeric vector. Standardized effect sizes μ/σ_0 where the expected weights of evidence is desired. Default: |
n.fixed |
Positive integer. Prefixed sample size. Default: 20. |
sigma0 |
Positive numeric. Known standard deviation in the population. Default: 1. |
nReplicate |
Positve integer. Number of replicated studies based on which the expected weights of evidence is calculated. Default: 50,000. |
nCore |
Positive integer. Default: One less than the total number of available cores. |
A list with two components named summary and BF.
$summary is a data frame with columns effect.size containing the values in es and avg.logBF containing the expected log(Hajnal's ratios) at those values.
$BF is a matrix of dimension length(es) by nReplicate. Each row contains the Hajnal's ratios at the corresponding standardized effec size in nReplicate replicated studies.
Sandipan Pramanik and Valen E. Johnson
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].
1 | out = fixedHajnal.onez_n(n.fixed = 20, es = c(0, 0.3), nCore = 1)
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