BFrlogOR {BayesRep}

Generalized replication Bayes factor for logOR effect sizes

Description

Computes the generalized replication Bayes factor for log odds ratio (logOR) effect sizes

Usage

BFrlogOR(
  ao,
  bo,
  nTo = ao + bo,
  co,
  do,
  nCo = co + do,
  ar,
  br,
  nTr = ar + br,
  cr,
  dr,
  nCr = cr + dr,
  ss,
  method = c("integration", "hypergeo")
)

Arguments

ao

Number of cases in original study treatment group

bo

Number of non-cases in original study treatment group

nTo

Number of participants in original study treatment group (specify alternatively to b)

co

Number of cases in original study control group

do

Number of non-cases in original study control group

nCo

Number of participants in original study control group (specify alternatively to d)

ar

Number of cases in replication study treatment group

br

Number of non-cases in replication study treatment group

nTr

Number of participants in replication study treatment group (specify alternatively to b)

cr

Number of cases in replication study control group

dr

Number of non-cases in replication study control group

nCr

Number of participants in replication study control group (specify alternatively to d)

ss

Standard deviation of the sceptical prior under H_\mathrm{S}. Defaults to 0

method

Method to compute posterior density. Either "integration" (default) or "hypergeo"

Details

This function computes the generalized replication Bayes factor for log odds ratio (logOR) effect sizes using an exact binomial likelihood for the data instead of the normal approximation used in BFr (for details, see Section 4 in Pawel and Held, 2022).

Value

The generalized replication Bayes factor \mathrm{BF}_{\mathrm{SA}}. \mathrm{BF}_{\mathrm{SA}} < 1 indicates that the data favour the advocate's hypothesis H_{\mathrm{A}} (replication success), whereas \mathrm{BF}_{\mathrm{SA}} > 1 indicates that the data favour the sceptic's hypothesis H_{\mathrm{S}} (replication failure).

Author(s)

Samuel Pawel

References

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

Pawel, S. and Held, L. (2022). The sceptical Bayes factor for the assessment of replication success. Journal of the Royal Statistical Society Series B: Statistical Methodology, 84(3): 879-911. doi:10.1111/rssb.12491

Examples

data("SSRPexact")
balafoutas2012 <- subset(SSRPexact, study == "Balafoutas and Sutter (2012), Science")
with(balafoutas2012,
     BFrlogOR(ao = ao, bo = bo, co = co, do = do, ar = ar, br = br, cr = cr, dr = dr,
              ss = 0))