BFe {BayesRep} | R Documentation |
Equality of effect size Bayes factor
Description
Computes the equality of effect size Bayes factor
Usage
BFe(to, so, tr, sr, tau, log = FALSE)
Arguments
to |
Original effect estimate |
so |
Standard error of the original effect estimate |
tr |
Replication effect estimate |
sr |
Standard error of the replication effect estimate |
tau |
The heterogeneity standard deviation |
log |
Logical indicating whether the natural logarithm of the Bayes
factor should be returned. Defaults to |
Details
The equality of effect size Bayes factor is the Bayes factor
contrasting the hypothesis of equal original and replication effect sizes
to the hypothesis
of unequal effect sizes
. Under the hypothesis of unequal effect sizes
the
study specific effect sizes are assumed to be normally distributed around
an overall effect size with heterogeneity standard deviation
tau
.
Value
The equality of effect size Bayes factor
.
indicates that the data favour the hypothesis of equal effect sizes
(replication success), whereas
indicates that the data favour the hypothesis of unequal
effect sizes
(replication failure).
Author(s)
Samuel Pawel
References
Bayarri, M. and Mayorall, A. (2002). Bayesian Design of "Successful" Replications. The American Statistician, 56(3): 207-214. doi:10.1198/000313002155
Verhagen, J. and Wagenmakers, E. J. (2014). Bayesian tests to quantify the result of a replication attempt. Journal of Experimental Psychology: General, 145:1457-1475. doi:10.1037/a0036731
Examples
## strong evidence for unequal effect sizes
BFe(to = 1, tr = 0.5, so = sqrt(1/100), sr = sqrt(1/100), tau = 0.3)
## some evidence for equal effect sizes
BFe(to = 1, tr = 1, so = sqrt(1/200), sr = sqrt(1/200), tau = 0.3)