| snapshot_naive {puniform} | R Documentation |
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 R.C.M.vanAert@tilburguniversity.edu
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))