In many meta-analysis cases the estimator of the overall effect in independent trials or experiments leads to unjustified significant results. This paper considers trials with two arms where the summary statistic of interest is either the mean difference or the risk difference. By using...

Many Information Theoretic Measures have been proposed for a quantitative assessment of causality relationships. While Gouriéroux, Monfort, and Renault (1987) had introduced the so-called “Kullback Causality Measures,” extending Geweke’s (1982) work in the context of Gaussian VAR...

An important but often overlooked obstacle in multivariate discrete data models is the specification of endogenous covariates. Endogeneity can be modeled as latent or observed, representing competing hypotheses about the outcomes being considered. However, little attention has been applied to...

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing...

Given several studies (inputs) of some phenomenon of interest, each input presents an estimate of a key parameter with an associated estimated precision. The random-effects model used in meta-analysis estimates this parameter based on a decomposition of the error term into within-input noise and...