Package: MetaIntegration 0.1.3

Michael Kleinsasser

MetaIntegration: Ensemble Meta-Inference Framework

An ensemble meta-inference framework to integrate multiple regression models into a current study. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2021) <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.

Authors:Tian Gu [aut], Bhramar Mukherjee [aut], Michael Kleinsasser [cre]

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MetaIntegration.pdf |MetaIntegration.html
MetaIntegration/json (API)

# Install 'MetaIntegration' in R:
install.packages('MetaIntegration', repos = c('https://umich-biostatistics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/umich-biostatistics/metaintegration/issues

On CRAN:

2.70 score 1 stars 1 scripts 203 downloads 9 exports 9 dependencies

Last updated 3 years agofrom:c7c80d84de. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 09 2024
R-4.5-winNOTEOct 09 2024
R-4.5-linuxNOTEOct 09 2024
R-4.4-winNOTEOct 09 2024
R-4.4-macNOTEOct 09 2024
R-4.3-winNOTEOct 09 2024
R-4.3-macNOTEOct 09 2024

Exports:asympVar_LinRegasympVar_LogRegexpitfxnCC_LinRegfxnCC_LogRegget_gamma_EBget_OCWget_SCLearnerget_var_EB

Dependencies:corpcorevaluatehighrknitrMASSRsolnptruncnormxfunyaml