Ensemble Meta-Prediction Framework
Overview
An ensemble meta-prediction framework to integrate multiple regression models into a current study. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2020) arXiv:2010.09971. A meta-analysis framework along with two weighted estimators as the ensemble of empirical Bayes estimators, which combines the estimates from the different external models. The proposed framework is flexible and robust in the ways that (i) it is capable of incorporating external models that use a slightly different set of covariates; (ii) it is able to identify the most relevant external information and diminish the influence of information that is less compatible with the internal data; and (iii) it nicely balances the bias-variance trade-off while preserving the most efficiency gain. The proposed estimators are more efficient than the naive analysis of the internal data and other naive combinations of external estimators.
Install
Health
NOTERd filesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64
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checkRd: (-1) get_gamma_EB.Rd:21: Lost braces in \itemize; \value handles \item{}{} directlyNOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Michael Kleinsasser <mkleinsa@umich.edu>’ The Description field contains (2020) <arXiv:2010.09971>. A meta-analysis framework along with two Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from: ‘knitr’ All declared Imports should be used.
- NOTE13 NOTENow
- NOTE14 NOTE2026-03-10
Documentation
- Help pages
- 9
- Examples that run
- 75%6 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 89%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 78%
Downloads
Repository
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Checks run against github.com/umich-biostatistics/metaintegration on 2026-10-11.
Dependencies
Installing MetaIntegration adds 17 packages (8 with compiled code, 5.1 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, knitr 479 KB.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
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- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.1.2Latest
- 0.1.12020-11-20
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-11-20
- Total releases
- 2 / 6 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 17 KB
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