meta.shrinkage: An R Package for Meta-Analyses for Simultaneously Estimating Individual Means

ALGORITHMS(2022)

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Abstract
Meta-analysis is an indispensable tool for synthesizing statistical results obtained from individual studies. Recently, non-Bayesian estimators for individual means were proposed by applying three methods: the James-Stein (JS) shrinkage estimator, isotonic regression estimator, and pretest (PT) estimator. In order to make these methods available to users, we develop a new R package meta.shrinkage. Our package can compute seven estimators (named JS, JS+, RML, RJS, RJS+, PT, and GPT). We introduce this R package along with the usage of the R functions and the "average-min-max" steps for the pool-adjacent violators algorithm. We conduct Monte Carlo simulations to validate the proposed R package to ensure that the package can work properly in a variety of scenarios. We also analyze a data example to show the ability of the R package.
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Key words
statistical decision theory,isotonic regression,meta-analysis,pretest estimator,restricted parameters,shrinkage estimation
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