pbf function

Product Bayes Factor

The product Bayes factor (PBF) aggregates evidence for an informative hypothesis across conceptual replication studies without imposing assumptions about heterogeneity.

pbf(...)

## Default S3 method:
pbf(x, ...)

## S3 method for class 'numeric'
pbf(yi, vi, ni, hypothesis = "y = 0", ...)

Arguments

• ...: Additional arguments passed to bain.
• x: An object for which a method exists, see Details.
• yi: Numeric vector with the observed effect sizes.
• vi: Numeric vector with the observed sampling variances.
• ni: Integer vector with the sample sizes.
• hypothesis: A character string containing the informative hypotheses to evaluate.

Returns

A data.frame of class pbf.

Details

Currently, the argument x accepts either: * A list of bain objects, resulting from a call to bain. * A list of model objects for which a bain method exists; in this case, pbf will call bain on these model objects before aggregating the Bayes factors.

Examples

pbf(yi = c(-.33, .32, .39, .31),
    vi = c(.085, .034, .016, .071),
    ni = c(7, 10, 13, 20))

References

Van Lissa, C. J., Kuiper, R. M., & Clapper, E. (2023, April 25). Aggregating evidence from conceptual replication studies using the product Bayes factor. tools:::Rd_expr_doi("10.31234/osf.io/nvqpw")