Generalised Inference in the Random Effects Meta Regression
Model
Provides methods for making inference in the random
effects meta regression model, such as point estimates and
confidence intervals for the heterogeneity parameter and the
regression coefficients vector.

Inference in Meta Analysis and Meta Regression
Provides methods for making inference in the random effects meta
regression model, such as point estimates and confidence intervals for the
heterogeneity parameter and the regression coefficients vector.  Inference
method are based on different statistical approaches.  Also includes tools
to run extensive simulation studies in parallel on high performance
clusters.  This allows for extensive testing of current inference methods
with new and state-of-the-art methods.  Functions for evaluating the
performance of both point and interval estimates are provided.  Also, a
large collection of different pre-defined plotting functions is implemented
in a ready-to-use fashion.
Thomas W. D. Möbius <kontakt@thomasmoebius.de>
MASS, lhs, plyr, BBmisc, ParamHelpers, BatchJobs,
BatchExperiments, ggplot2, metafor
'example-bcg.R' 'methods-for-batch-distribution.R'
'methods-for-data-generation.R' 'methods-for-experiments.R'
'methods-for-inference.R' 'plot-functions.R'
'plot-interval-estimates.R' 'plot-pivotal-distributions.R'
'plot-point-estimates.R' 'zzz.R'

Provides methods for making inference in the random effects meta
regression model such as point estimates and confidence intervals for the
heterogeneity parameter and the regression coefficients vector.  Inference
methods are based on different approaches to statistical inference.
Methods from three different schools are included: methods based on the
method of moments approach, methods based on likelihood, and methods based
on generalised inference.  The package also includes tools to run extensive
simulation studies in parallel on high performance clusters in a modular
way.  This allows extensive testing of custom inferential methods with all
implemented state-of-the-art methods in a standardised way.  Tools for
evaluating the performance of both point and interval estimates are
provided.  Also, a large collection of different pre-defined plotting
functions is implemented in a ready-to-use fashion.