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.
- Version1.0.0
- R versionunknown
- LicenseMIT License
- Needs compilation?No
- Last release08/20/2016
Documentation
Team
David Stanley
Insights
Last 30 days
This package has been downloaded 140 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,285 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 217 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports4 packages