Alternative covariance structures for the between-study (co)variance matrix of random effects in multivariate meta-analysis or meta-regression, usually defined through the argument bscov of the function mvmeta.
mvmeta.vc
(Package: mvmeta) :
Variance Components Estimator for mvmeta Models
This function implements a variance components estimator for multivariate and univariate random-effects meta-analysis and meta-regression. It is meant to be used internally and not directly run by the users.
This method function computes predictions from fitted univariate or multivariate meta-analytical models represented in objects of class "mvmeta", optionally for a new set of predictor values in meta-regression models. Predictions are optionally accompanied by standard errors, confidence intervals or the entire (co)variance matrix of the predicted outcomes.
mlprof.fn
(Package: mvmeta) :
Likelihood Functions for mvmeta Models
These functions compute the value of the log-likelihood and the related vectors of first partial derivatives for random-effects multivariate and univariate meta-analysis and meta-regression, in terms of model parameters. They are meant to be used internally and not directly run by the users.
These method functions exclude rows corresponding to studies with invalid missing pattern from model frames of class "data.frame.mvmeta". This guarantees the correct handling of missing values while fitting multivariate and univariate meta-analytical models.
mvmeta
(Package: mvmeta) :
Fitting Multivariate and Univariate Meta-Analysis and Meta-Regression Models
The function mvmeta performs fixed and random-effects multivariate and univariate meta-analysis and meta-regression, with various estimation methods. The function mvmeta.fit is a wrapper for actual fitting functions based on different estimation methods, usually called internally. See mvmeta-package for an overview.
qtest.mvmeta
(Package: mvmeta) :
Cochran Q Test of Heterogeneity for mvmeta Models
This method function performs a Cochran Q test of (residual) heterogeneity on fitted univariate or multivariate meta-analytical models represented in objects of class "mvmeta".
coef.mvmeta
(Package: mvmeta) :
Extract Coefficients and (Co)Variance Matrix from mvmeta Objects
These method functions return the estimated fixed-effects coefficients and their (co)variance matrix for fitted univariate or multivariate meta-analytical models represented in objects of class "mvmeta".
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