
In case of two independent populations
SBFHajnal_twot(es = c(0, 0.2, 0.3, 0.5), es1 = 0.3,
n1min = 2, n2min = 2, n1max = 5000, n2max = 5000,
RejectH1.threshold = exp(-3), RejectH0.threshold = exp(3),
batch1.size.increment, batch2.size.increment,
nReplicate = 50000, nCore)
Numeric vector. Standardized effect size differences c(0, 0.2, 0.3, 0.5)
.
Positive numeric.
Positive integer. Minimum sample size from Group-1 in the sequential comparison. Should be at least 2. Default: 1.
Positive integer. Minimum sample size from Group-2 in the sequential comparison. Should be at least 2. Default: 1.
Positive integer. Maximum sample size from Group-1 in the sequential comparison. Default: 1.
Positive integer. Maximum sample size from Group-2 in the sequential comparison. Default: 1.
Positive numeric. RejectH1.threshold
. Default: exp(-3)
.
Positive numeric. RejectH0.threshold
. Default: exp(3)
.
function. Increment in sample size from Group-1 at each sequential step. Default: function(narg){20}
. This means an increment of 20 samples at each step.
function. Increment in sample size from Group-2 at each sequential step. Default: function(narg){20}
. This means an increment of 20 samples at each step.
Positve integer. Number of replicated studies based on which the OC and ASN are calculated. Default: 50,000.
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.
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 = SBFHajnal_twot(n1max = 100, n2max = 100, es = c(0, 0.3), nCore = 1)
# }
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