snapshot_naive: snapshot_naive

In RobbievanAert/puniform: Meta-Analysis Methods Correcting for Publication Bias

snapshot_naive

Description

Function for applying Snapshot Bayesian Meta-Analysis Method (snapshot naive) for two-independent means and raw correlation coefficients.

Usage

snapshot_naive(ri, ni, m1i, m2i, n1i, n2i, sd1i, sd2i, tobs)

Arguments

ri	A vector of length two containing the raw correlation coefficients of the original study and replication
ni	A vector of length two containing the sample size of the original study and replication for the raw correlation coefficient
m1i	A vector of length two containing the means in group 1 for the original study and replication for two-independent means
m2i	A vector of length two containing the means in group 2 for the original and replication for two-independent means
n1i	A vector of length two containing the sample sizes in group 1 for the original study and replication for two-independent means
n2i	A vector of length two containing the sample sizes in group 2 for the original study and replication for two-independent means
sd1i	A vector of length two containing the standard deviations in group 1 for the original study and replication for two-independent means
sd2i	A vector of length two containing the standard deviations in group 2 for the original study and replication for two-independent means
tobs	A vector of length two containing the t-values of the original study and replication

Details

The function computes posterior probabilities (assuming a uniform prior distribution) for four true effect sizes (no, small, medium, and large) based on an original study and replication. For more information see van Aert and van Assen (2016).

Two different effect size measures can be used as input for the snapshot.naive function: two-independent means and raw correlation coefficients. Analyzing two-independent means can be done by either providing the function group means (m1i and m2i), standard deviations (sd1i and sd2i), and sample sizes (n1i and n2i) or t-values (tobs) and sample sizes (n1i and n2i).See the Example section for an example. Raw correlation coefficients can be analyzed by supplying ri and ni to the snapshot.naive.

Value

The snapshot.naive function returns a data frame with posterior probabilities for no (p.0), small (p.sm), medium (p.me), and large (p.la) true effect size.

Author(s)

Robbie C.M. van Aert [e-mail]

References

van Aert, R.C.M. & van Assen, M.A.L.M. (2017). Bayesian evaluation of effect size after replicating an original study. PLoS ONE, 12(4), e0175302. doi:10.1371/journal.pone.0175302

Examples

### Example as presented on page 491 in Maxwell, Lau, and Howard (2015)
snapshot_naive(ri = c(0.243, 0.114), ni = c(80, 172))

RobbievanAert/puniform documentation built on Sept. 22, 2023, 2:53 a.m.