PREFACE

Meta-analysis is a fundamental tool of modern evidence-based practice that enables researchers to systematically and statistically combine data from different studies to derive broader insights. Meta-analysis is the synthesis of many studies from an integrated perspective, and this Module seeks to explore the principles, designs, and applications of meta-analysis from its theoretical and practical applications in different fields.

With this Module we expect to accustom participants with the systematic and statistical principles that lead to high-quality meta-analyses and to be competent with different disciplines where this method applies.

It is carefully designed with content that provides an overview of the essentials of systematic reviews and meta-analysis, as well as procedural steps on how to conduct it, such as:

1. Ability To Critically Assess Research: Learn to evaluate the quality and reliability of primary studies, a crucial step to build an evidence base.
2. Combine Complex Data: Learn statistical methods to integrate and analyse different types of data, uncovering meaningful and generalizable insights.
3. Address Variability: Tackle the challenges of heterogeneity inherent in individual study designs and outcomes by employing advanced models, such as fixed-effect and random-effects models.
4. Bias Mitigation: Utilize methods to recognize and reduce publication bias, preserving the rigor of combined outcomes.
5. Enhance Decision Making: Derive actionable recommendations from meta-analytic results for policy, practice, and future research agendas.

This Module aims to equip learners or experienced researchers with the principles and instruments needed to perform meta-analyses of the highest quality, from systematic reviews and effect size estimation to model choice, and to cultivate a culture of evidence-based inquiry and innovation in answering complex research questions.