sampleSizeEdgington {ReplicationSuccess} | R Documentation |
Computes the required relative sample size to achieve replication success with Edgington's method based on power
Description
The relative sample size to achieve replication success with Edgington's method is computed based on the z-value (or one-sided p-value) of the original study, the significance level, the ratio of the weight of the replication study over the weight of the original study, the design prior and the power.
Usage
sampleSizeEdgington(
zo = NULL,
po = NULL,
r = 1,
power,
level = 0.025,
designPrior = "conditional",
shrinkage = 0
)
Arguments
zo |
Numeric vector of z-values from original studies. |
po |
Numeric vector of original one-sided p-values |
r |
Numeric vector of ratios of replication to original weight. |
power |
Power to achieve replication success. |
level |
One-sided significance level. Default is 0.025. |
designPrior |
Either "conditional" (default) or "predictive". |
shrinkage |
Numeric vector with values in [0,1). Defaults to 0.
Specifies the shrinkage of the original effect estimate towards zero,
e.g., the effect is shrunken by a factor of 25% for |
Details
Either zo
or po
must be specified.
Value
The relative sample size to achieve replication success with
Edgington's method. If impossible to achieve the desired power for
specified inputs NaN
is returned.
Author(s)
Charlotte Micheloud, Leonhard Held, Samuel Pawel
References
Held, L., Pawel, S., Micheloud, C. (2024). The assessment of replicability using the sum of p-values. Royal Society Open Science. 11(8):11240149. doi:10.1098/rsos.240149
Examples
## partially recreate Figure 5 from paper
poseq <- exp(seq(log(0.00001), log(0.025), length.out = 100))
cseq <- sampleSizeEdgington(po = poseq, power = 0.8)
cseqSig <- sampleSizeSignificance(zo = p2z(p = poseq, alternative = "one.sided"),
power = 0.8)
plot(poseq, cseq/cseqSig, log = "x", xlim = c(0.00001, 0.035), ylim = c(0.9, 1.3),
type = "l", las = 1, xlab = "Original p-value", ylab = "Sample size ratio")