remaCor
Random Effects Meta-Analysis for Correlated Test Statistics
Meta-analysis is widely used to summarize estimated effects sizes across multiple statistical tests. Standard fixed and random effect meta-analysis methods assume that the estimated of the effect sizes are statistically independent. Here we relax this assumption and enable meta-analysis when the correlation matrix between effect size estimates is known. Fixed effect meta-analysis uses the method of Lin and Sullivan (2009) doi:10.1016/j.ajhg.2009.11.001, and random effects meta-analysis uses the method of Han, et al. doi:10.1093/hmg/ddw049.
- Version0.0.18
- R versionunknown
- LicenseArtistic-2.0
- Needs compilation?Yes
- remaCor citation info
- Last release02/08/2024
Documentation
Team
Gabriel Hoffman
Insights
Last 30 days
This package has been downloaded 1,184 times in the last 30 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 39 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 12,484 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Sep 17, 2024 with 88 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
- Imports5 packages
- Suggests4 packages
- Linking To2 packages