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

predictionInterval_1.0.0.tar.gz
predictionInterval_1.0.0.zip(r-4.5)predictionInterval_1.0.0.zip(r-4.4)predictionInterval_1.0.0.zip(r-4.3)
predictionInterval_1.0.0.tgz(r-4.4-any)predictionInterval_1.0.0.tgz(r-4.3-any)
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predictionInterval.pdf |predictionInterval.html
predictionInterval/json (API)

# Install 'predictionInterval' in R:
install.packages('predictionInterval', repos = c('https://dstanley4.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

On CRAN:

3.08 score 1 stars 12 scripts 186 downloads 2 mentions 6 exports 54 dependencies

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

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-winOKNov 09 2024
R-4.5-linuxOKNov 09 2024
R-4.4-winOKNov 09 2024
R-4.4-macOKNov 09 2024
R-4.3-winOKNov 09 2024
R-4.3-macOKNov 09 2024

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

Dependencies:abindarmBHbootclicodacolorspacedigestfansifarverggplot2gluegtableisobandlabelinglatticelavaanlifecyclelme4magrittrMASSMatrixMBESSmgcvmiminqamnormtmunsellmvtnormnlmenloptrnumDerivOpenMxpbapplypbivnormpillarpkgconfigquadprogR6RColorBrewerRcppRcppEigenRcppParallelrlangrpfscalessemsemToolsStanHeaderstibbleutf8vctrsviridisLitewithr