effectSizeReplicationSuccess: Computes the minimum relative effect size to achieve...

In ReplicationSuccess: Design and Analysis of Replication Studies

Computes the minimum relative effect size to achieve replication success with the sceptical p-value

Description

The minimum relative effect size (replication to original) to achieve replication success with the sceptical p-value is computed based on the result of the original study and the corresponding variance ratio.

Usage

effectSizeReplicationSuccess(
  zo,
  c = 1,
  level = 0.025,
  alternative = c("one.sided", "two.sided"),
  type = c("golden", "nominal", "controlled")
)

Arguments

zo	Numeric vector of z-values from original studies.
c	Numeric vector of variance ratios of the original and replication effect estimates. This is usually the ratio of the sample size of the replication study to the sample size of the original study.
level	Threshold for the calibrated sceptical p-value. Default is 0.025.
alternative	Specifies if level is "one.sided" (default) or "two.sided". If "one.sided", then effect size calculations are based on a one-sided assessment of replication success in the direction of the original effect estimate.
type	Type of recalibration. Can be either "golden" (default), "nominal" (no recalibration), or "controlled". "golden" ensures that for an original study just significant at the specified level, replication success is only possible for replication effect estimates larger than the original one. "controlled" ensures exact overall Type-I error control at level level^2.

Details

effectSizeReplicationSuccess is the vectorized version of the internal function .effectSizeReplicationSuccess_. Vectorize is used to vectorize the function.

Value

The minimum relative effect size to achieve replication success with the sceptical p-value.

Author(s)

Leonhard Held, Charlotte Micheloud, Samuel Pawel, Florian Gerber

References

Held, L., Micheloud, C., Pawel, S. (2022). The assessment of replication success based on relative effect size. The Annals of Applied Statistics. 16:706-720. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/21-AOAS1502")}

Micheloud, C., Balabdaoui, F., Held, L. (2023). Beyond the two-trials rule: Type-I error control and sample size planning with the sceptical p-value. https://arxiv.org/abs/2207.00464

See Also

sampleSizeReplicationSuccess, levelSceptical

Examples

po <- c(0.001, 0.002, 0.01, 0.02, 0.025)
zo <- p2z(po, alternative = "one.sided")

effectSizeReplicationSuccess(zo = zo, c = 1, level = 0.025,
                             alternative = "one.sided", type = "golden")

effectSizeReplicationSuccess(zo = zo, c = 10, level = 0.025,
                             alternative = "one.sided", type = "golden")
effectSizeReplicationSuccess(zo = zo, c = 10, level = 0.025,
                             alternative = "one.sided", type = "controlled")
effectSizeReplicationSuccess(zo = zo, c= 2, level = 0.025,
                             alternative = "one.sided", type = "nominal")

effectSizeReplicationSuccess(zo = zo, c = 2, level = 0.05,
                             alternative = "two.sided", type = "nominal")

ReplicationSuccess documentation built on April 3, 2023, 5:11 p.m.