sampleSizeReplicationSuccess {ReplicationSuccess}R Documentation

Computes the required relative sample size to achieve replication success with a certain power

Description

The relative sample size for replication success is computed based on the z-value of the original study, the power, and the design prior.

Usage

sampleSizeReplicationSuccess(zo, 
                             power, 
                             level = thresholdSceptical(level = 0.025, 
                                                        alternative = alternative, 
                                                        type = "golden"),
                             designPrior = "conditional",
                             alternative = "one.sided")

Arguments

zo

A vector of z-values from original studies.

power

The power to achieve replication success.

level

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

designPrior

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

alternative

Either "one.sided" or "two.sided". Defaults to "one.sided". If "one.sided", then sample size calculations are based on a one-sided assessment of replication success in the direction of the original effect estimate.

Value

The relative sample size for replication success. If larger than 1000 Inf is returned.

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

pSceptical, powerReplicationSuccess, thresholdSceptical

Examples



sampleSizeReplicationSuccess(zo = p2z(0.005), power = 0.8)
sampleSizeReplicationSuccess(zo = p2z(0.005), power = 0.8, 
                             designPrior = "predictive")
thresNominal <- 0.025
sampleSizeReplicationSuccess(zo = p2z(0.005), power = 0.8, 
                             level = thresNominal,
                             alternative = "one.sided")
sampleSizeReplicationSuccess(zo = p2z(0.005), power = 0.8, 
                             level = thresNominal,
                             alternative = "one.sided", 
                             designPrior = "predictive")

[Package ReplicationSuccess version 0.1-3 Index]