
  Random draws of heteroscedasticity responses of studies,
  where each study in a random effects meta regression
  model follows a Gaussian response. Thus D = (d * X) /
  (s-1) where X is chi-squared distributed.


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.

rD: Data generation: Gaussian-Gaussian model

Description

Usage

Arguments

Value

Examples