A common problem faced by journal reviewers and authors is the question of whether the results of a replication study are consistent with the original published study. One solution to this problem is to examine the effect size from the original study and generate the range of effect sizes that could reasonably be obtained (due to random sampling) in a replication attempt (i.e., calculate a prediction interval). This package has functions that calculate the prediction interval for the correlation (i.e., r), standardized mean difference (i.e., d-value), and mean.

Version: | 1.0.0 |

Imports: | ggplot2, MBESS, MASS, stats, pbapply |

Published: | 2016-08-20 |

Author: | David Stanley |

Maintainer: | David Stanley <dstanley at uoguelph.ca> |

License: | MIT License + file LICENSE |

NeedsCompilation: | no |

Materials: | README |

CRAN checks: | predictionInterval results |

Reference manual: | predictionInterval.pdf |

Package source: | predictionInterval_1.0.0.tar.gz |

Windows binaries: | r-prerelease: predictionInterval_1.0.0.zip, r-release: predictionInterval_1.0.0.zip, r-oldrel: predictionInterval_1.0.0.zip |

macOS binaries: | r-prerelease: predictionInterval_1.0.0.tgz, r-release: predictionInterval_1.0.0.tgz, r-oldrel: predictionInterval_1.0.0.tgz |

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