Description Usage Arguments Value Author(s) References Examples
In a N(μ,σ^2) population with unknown variance σ^2, consider the two-sided one-sample t-test for testing the point null hypothesis H_0 : μ = 0 against H_1 : μ \neq 0. This function calculates the operating characteristics (OC) and average sample number (ASN) of the Sequential Bayes Factor design when the prior assumed on the standardized effect size μ/σ under the alternative places equal probability at +δ and -δ (δ>0 prefixed).
1 2 3 4 | SBFHajnal_onet(es = c(0, 0.2, 0.3, 0.5), es1 = 0.3,
nmin = 2, nmax = 5000,
RejectH1.threshold = exp(-3), RejectH0.threshold = exp(3),
batch.size.increment, nReplicate = 50000, nCore)
|
es |
Numeric vector. Standardized effect sizes μ/σ where OC and ASN are desired. Default: |
es1 |
Positive numeric. δ as above. Default: 0.3. For this, the prior on the standardized effect size μ/σ takes values 0.3 and -0.3 each with equal probability 1/2. |
nmin |
Positive integer. Minimum sample size in the sequential comparison. Should be at least 2. Default: 1. |
nmax |
Positive integer. Maximum sample size in the sequential comparison. Default: 1. |
RejectH1.threshold |
Positive numeric. H_0 is accepted if BF ≤ |
RejectH0.threshold |
Positive numeric. H_0 is rejected if BF ≥ |
batch.size.increment |
function. Increment in sample size at each sequential step. Default: |
nReplicate |
Positve integer. Number of replicated studies based on which the OC and ASN are calculated. Default: 50,000. |
nCore |
Positive integer. Default: One less than the total number of available cores. |
A list with three components named summary
, BF
, and N
.
$summary
is a data frame with columns effect.size
containing the values in es
. At those values, acceptH0
contains the proportion of times H_0
is accepted, rejectH0
contains the proportion of times H_0
is rejected, inconclusive
contains the proportion of times the test is inconclusive, ASN
contains the ASN, and avg.logBF
contains the expected weight of evidence values.
$BF
is a matrix of dimension length(es)
by nReplicate
. Each row contains the Bayes factor values at the corresponding standardized effec size in nReplicate
replicated studies.
$N
is a matrix of the same dimension as $BF
. Each row contains the sample size required to reach a decision 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 = SBFHajnal_onet(nmax = 50, es = c(0, 0.3), nCore = 1)
|
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