blup

an object for which BLUPs are meaningful. See <squote>Details</squote>.

The function <code>blup</code> is generic. It can be used to compute the best linear unbiased predictions (BLUPs) for specific classes of objects. BLUPs combine the fitted values based on the fixed effects in the model and the estimated contributions of the random effects.

methods

The metafor package provides a comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects (conditional) logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted.

blup: Compute Best Linear Unbiased Predictions

Description

Usage

Arguments

Value

Details

References

See Also