Package: predictionInterval 1.0.0

predictionInterval: Prediction Interval Functions for Assessing Replication Study Results

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.

Authors:David Stanley

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predictionInterval.pdf |predictionInterval.html✨
predictionInterval/json (API)

Peer review:

Bug tracker:https://github.com/dstanley4/predictioninterval/issues

On CRAN:

6 exports 1 stars 1.25 score 54 dependencies 2 mentions 12 scripts 130 downloads

Last updated 8 years agofrom:47da4b41f5. Checks:OK: 7. Indexed: yes.

Exports:pi.dpi.d.demopi.mpi.m.demopi.rpi.r.demo

Dependencies:abindarmBHbootclicodacolorspacedigestfansifarverggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixMBESSmgcvmiminqamnormtmunsellmvtnormnlmenloptrnumDerivOpenMxpbapplypbivnormpillarpkgconfigquadprogR6RColorBrewerRcppRcppEigenRcppParallelrlangrpfscalessemsemToolsStanHeaderstibbleutf8vctrsviridisLitewithr