Related Experiment Video
Updated: Aug 6, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
A Practical Guide to Evidence Synthesis: Meta-Analysis, Network Meta-Analysis, Meta-Regressions and Beyond
Yu-Kang Tu1,2,3, Roberto Farina4, Alessandra Viola4
1Institute of Health Data Analytics & Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan.
None:
Meta-analysis has become an indispensable tool in medical and dental research, providing an estimate of treatment efficacy or harm by combining data from all relevant studies identified by a systematic review. Meta-analysis produces evidence at the highest level of the study design hierarchy. Meta-analysis is a broad term for a set of statistical tools used to analyse data across a range of research questions. Different research questions have different criteria for selecting relevant studies and extracting and organising data in different forms and require different statistical approaches to synthesising the data. This article focuses on meta-analysis for comparing interventions. We use plain but precise language to explain the statistical concepts and assumptions underlying these methods. This article is divided into three parts. We begin with statistical models for and key assumptions of standard pairwise meta-analysis, comparing two treatment groups. We then extend our discussion to network meta-analysis, comparing multiple treatment groups. Finally, we discuss a few issues that arise in selecting studies and preparing data for a meta-analysis. Throughout, we use examples from periodontal regeneration; all analyses were conducted using the free statistical software R. We strongly encourage close collaboration between periodontal researchers and experienced statisticians when planning and conducting meta-analyses.
Related Concept Videos
Introduction to Epidemiology
The Evidence for Evolution
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Hazard Ratio
For example, in a clinical trial evaluating a...
Confounding in Epidemiological Studies
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...