rema: Rare Event Meta Analysis
The rema package implements a permutation-based approach for binary meta-analyses of 2x2 tables, founded on conditional logistic regression, that provides more reliable statistical tests when heterogeneity is observed in rare event data (Zabriskie et al. 2021 <doi:10.1002/sim.9142>). To adjust for the effect of heterogeneity, this method conditions on the sufficient statistic of a proxy for the heterogeneity effect as opposed toestimating the heterogeneity variance. While this results in the model notstrictly falling under the random-effects framework, it is akin to a random-effects approach in that it assumes differences in variability due to treatment. Further, this method does not rely on large-sample approximations or continuity corrections for rare event data. This methoduses the permutational distribution of the test statistic instead ofasymptotic approximations for inference. The number of observed events drives the computation complexity for creating this permutational distribution. Accordingly, for this method to be computationally feasible,it should only be applied to meta-analyses with a relatively low number ofobserved events. To create this permutational distribution, a network algorithm, based on the work of Mehta et al. (1992) <doi:10.2307/1390598> and Corcoran et al. (2001) <doi:10.1111/j.0006-341x.2001.00941.x>, is employed using C++ and integrated into the package.
| Version: | 0.0.1 |
| Depends: | R (≥ 2.10) |
| Imports: | graphics,Rcpp,Rdpack, stats |
| LinkingTo: | Rcpp,progress |
| Suggests: | testthat (≥ 3.0.0),knitr,rmarkdown |
| Published: | 2021-10-28 |
| DOI: | 10.32614/CRAN.package.rema |
| Author: | Brinley N. Zabriskie [aut, cre], Benjamin Kinard [aut], Chris Sypherd [aut], Ryan Whetten [aut], Madeleine Hays [ctb] |
| Maintainer: | Brinley N. Zabriskie <zabriskie at stat.byu.edu> |
| License: | GPL (≥ 3) | fileLICENSE |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| In views: | MetaAnalysis |
| CRAN checks: | rema results |
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