The present method provides an expected sample size such that compelling evidence in the form of a Bayes factor can be collected for a given effect size with a certain long-run probability when allowing for sequential testing.
Usage
ssp_bfda(
tpr = 0.8,
delta,
thresh = 10,
n_rep = 1000,
prior_scale = 1/sqrt(2),
max_n = 1500
)Arguments
- tpr
Numeric. The long-run probability of obtaining a Bayes factor at least as high as the critical threshold favoring superiority, given Delta.
- delta
Numeric. The expected population effect size.
- thresh
Integer. The Bayes factor threshold for inference.
- n_rep
Integer. The number of simulations.
- prior_scale
Numeric. Scale of the Cauchy prior distribution.
- max_n
Integer. The maximum number of participants per group (both groups are assumed to have equal sample size).
Value
The function returns a list of four named numeric vectors. The first `tpr` is the range of TPRs that were provided as a parameter. The second `n1` is the range of determined sample sizes for the given design. The third `h0` is the frequency of Bayes factor providing evidence with the given threshold for the null hypothesis. The fourth `ha` is the same as `h0` but for the alternative hypothesis.