powerReplicationSuccess {ReplicationSuccess}R Documentation

Computes the power for replication success

Description

The power for replication success is computed based on the result of the original study, the corresponding variance ratio and the design prior.

Usage

powerReplicationSuccess(zo, 
                        c = 1, 
                        level = thresholdSceptical(level = 0.025, 
                                                   alternative = alternative,
                                                   type = "golden"),
                        designPrior = "conditional", 
                        alternative = "one.sided")

Arguments

zo

A vector of z-values from original studies.

c

A 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

Replication success level. Default is the golden level (0.062 for one-sided level = 0.025).

designPrior

Either "conditional" or "predictive". Defaults to "conditional".

alternative

Either "one.sided" or "two.sided". Defaults to "one.sided". Specifies if the p-value is one-sided or two-sided. If "one.sided", then power calculations are based on a one-sided assessment of replication success in the direction of the original effect estimate.

Value

The power for replication success.

Author(s)

Leonhard Held

References

Held, L. (2020). A new standard for the analysis and design of replication studies (with discussion). Journal of the Royal Statistical Society: Series A (Statistics in Society). 183(2):431 - 448. https://doi.org/10.1111/rssa.12493

See Also

sampleSizeReplicationSuccess, pSceptical, thresholdSceptical

Examples


powerReplicationSuccess(zo = p2z(0.005), c = 2)
powerReplicationSuccess(zo = p2z(0.005), c = 2, designPrior = "predictive")
thresNominal <- thresholdSceptical(0.025, type = "nominal")
powerReplicationSuccess(zo = p2z(0.005), c = 2, level = thresNominal)
powerReplicationSuccess(zo = p2z(0.005), c = 2, level = thresNominal, 
                        designPrior = "predictive")

powerReplicationSuccess(zo = p2z(0.005), c = 1/2)
powerReplicationSuccess(zo = p2z(0.005), c = 1/2, designPrior = "predictive")
powerReplicationSuccess(zo = p2z(0.005), c = 1/2, level = thresNominal)
powerReplicationSuccess(zo = p2z(0.005), c = 1/2, level = thresNominal, 
                        designPrior = "predictive")


[Package ReplicationSuccess version 0.1-3 Index]