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Generates empirical Bayes (EB) estimates, also known as best linear unbiased predictions (BLUPs), by merging the fitted values obtained from fixed effects and estimated contributions of random effects. These estimates represent the study-specific true effect sizes or outcomes and are accompanied by standard errors and prediction interval bounds. Uses the metafor::blup.rma.uni() function internally.


# S3 method for runMetaAnalysis
blup(x, which = NULL, ...)



An object of class runMetaAnalysis.


Model for which estimates should be printed. Can be one of "overall", "combined", "lowest.highest", "outliers", "influence", "threelevel", or "threelevel.che".


Additional arguments.