STAREG
An Empirical Bayes Approach for Replicability Analysis Across Two Studies
A robust and powerful empirical Bayesian approach is developed for replicability analysis of two large-scale experimental studies. The method controls the false discovery rate by using the joint local false discovery rate based on the replicability null as the test statistic. An EM algorithm combined with a shape constraint nonparametric method is used to estimate unknown parameters and functions. [Li, Y. et al., (2023),
- Version1.0.3
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Last release08/15/2023
Team
Yan Li
MaintainerShow author detailsXianyang Zhang
Show author detailsRolesAuthorXiang Zhou
Show author detailsRolesAuthorHongyuan Cao
Show author detailsRolesAuthor, ContributorRui Chen
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 158 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 2,063 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 Sep 11, 2024 with 23 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
- Depends1 package
- Linking To2 packages