Package: ReplicationSuccess 1.3.2

Samuel Pawel

ReplicationSuccess: Design and Analysis of Replication Studies

Provides utilities for the design and analysis of replication studies. Features both traditional methods based on statistical significance and more recent methods such as the sceptical p-value; Held L. (2020) <doi:10.1111/rssa.12493>, Held et al. (2022) <doi:10.1214/21-AOAS1502>, Micheloud et al. (2023) <doi:10.1111/stan.12312>. Also provides related methods including the harmonic mean chi-squared test; Held, L. (2020) <doi:10.1111/rssc.12410>, and intrinsic credibility; Held, L. (2019) <doi:10.1098/rsos.181534>. Contains datasets from five large-scale replication projects.

Authors:Leonhard Held [aut], Samuel Pawel [cre], Charlotte Micheloud [aut], Florian Gerber [aut], Felix Hofmann [aut]

ReplicationSuccess_1.3.2.tar.gz
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ReplicationSuccess.pdf |ReplicationSuccess.html✨
ReplicationSuccess/json (API)
NEWS

# Install 'ReplicationSuccess' in R:
install.packages('ReplicationSuccess', repos = c('https://crsuzh.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/crsuzh/replicationsuccess/issues

Datasets:
  • RProjects - Data from four large-scale replication projects
  • SSRP - Data from the Social Sciences Replication Project
  • protzko2020 - Data from Protzko et al.

On CRAN:

29 exports 1 stars 1.26 score 0 dependencies 36 scripts 269 downloads

Last updated 7 months agofrom:82f4d07231. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 23 2024
R-4.5-winOKAug 23 2024
R-4.5-linuxOKAug 23 2024
R-4.4-winOKAug 23 2024
R-4.4-macOKAug 23 2024
R-4.3-winOKAug 23 2024
R-4.3-macOKAug 23 2024

Exports:ci2estimateci2pci2seci2zeffectSizeReplicationSuccesseffectSizeSignificancehMeanChiSqhMeanChiSqCIhMeanChiSqMulevelScepticalp2zpBoxpIntrinsicpowerReplicationSuccesspowerSignificancepowerSignificanceInterimPPpScepticalpredictionIntervalpReplicatepScepticalpvalueBoundQtestsampleSizeReplicationSuccesssampleSizeSignificanceT1EpScepticalthresholdIntrinsicz2pzBoxzSceptical

Dependencies:

Introduction to ReplicationSuccess

Rendered fromReplicationSuccess.Rnwusingknitr::knitron Aug 23 2024.

Last update: 2023-04-01
Started: 2021-06-14

Readme and manuals

Help Manual

Help pageTopics
Convert between estimates, z-values, p-values, and confidence intervalsci2estimate ci2p ci2se ci2z p2z z2p
Computes the minimum relative effect size to achieve replication success with the sceptical p-valueeffectSizeReplicationSuccess
Computes the minimum relative effect size to achieve significance of the replication studyeffectSizeSignificance
harmonic mean chi-squared testhMeanChiSq hMeanChiSqCI hMeanChiSqMu
Computes the replication success levellevelSceptical
Computes Box's tail probabilitypBox zBox
Computes the p-value for intrinsic credibilitypIntrinsic
Computes the power for replication success with the sceptical p-valuepowerReplicationSuccess
Computes the power for significancepowerSignificance
Interim power of a replication studypowerSignificanceInterim
Compute project power of the sceptical p-valuePPpSceptical
Prediction interval for effect estimate of replication studypredictionInterval
Probability of replicating an effect by Killeen (2005)pReplicate
Data from Protzko et al. (2020)protzko2020
Computes the sceptical p-value and z-valuepSceptical zSceptical
Bound for the p-values entering the harmonic mean chi-squared testpvalueBound
Q-test to assess compatibility between original and replication effect estimateQtest
Data from four large-scale replication projectsRProjects
Computes the required relative sample size to achieve replication success with the sceptical p-valuesampleSizeReplicationSuccess
Computes the required relative sample size to achieve significance based on powersampleSizeSignificance
Data from the Social Sciences Replication ProjectSSRP
Compute overall type-I error rate of the sceptical p-valueT1EpSceptical
Computes the p-value threshold for intrinsic credibilitythresholdIntrinsic