Using Bayesian Meta-Regression to Advance Prevention Science Research: an Introduction and Empirical Illustration. Academic Article

abstract

• Driven by the movement of evidence-based practices, Bayesian statistical methods have become increasingly popular. This paper introduces a Bayesian approach to meta-regression, focusing on the use and implementation in prevention science research. We first compare Bayesian meta-analysis and meta-regression to a frequentist approach. Thereafter, we illustrate Bayesian methods in meta-regression, highlighting advantages, providing detailed interpretation, and presenting results. The example is completed using several R packages. We also provide annotated R code for readers as a foundation for their own research.

authors

• Ettekal, Idean
• Thompson, Christopher

published proceedings

• Prev Sci

altmetric score

• 0.5

author list (cited authors)

• Thompson, C. G., Semma, B., Wang, N., & Ettekal, I.

citation count

• 3

complete list of authors

• Thompson, Christopher G||Semma, Brandie||Wang, Naike||Ettekal, Idean

publication date

• April 2022

publisher

• Springer Nature  Publisher

published in

• Prevention Science  Journal

keywords

• Bayes Theorem
• Bayesian Methods
• Health Services Research
• Humans
• Meta-Analysis As Topic
• Meta-analysis
• Meta-regression

PubMed Central ID

• 35316455

Digital Object Identifier (DOI)

• 10.1007/s11121-021-01330-8

start page

• 455

end page

• 466

volume

• 23

issue

• 3

URL

• http://dx.doi.org/10.1007/s11121-021-01330-8