Modern Biostatistical Methods for Evidence-Based Global Health Research

This book provides an overview of the emerging topics in biostatistical theories and methods through their applications to evidence-based global health research and decision-making. It brings together some of the top scholars engaged in biostatistical method development on global health to highlight and describe recent advances in evidence-based global health applications. The volume is composed of five main parts: data harmonization and analysis; systematic review and statistical meta-analysis; spatial-temporal modeling and disease mapping; Bayesian statistical modeling; and statistical methods for longitudinal data or survival data.

It is designed to be illuminating and valuable to both expert biostatisticians and to health researchers engaged in methodological applications in evidence-based global health research. It is particularly relevant to countries where global health research is being rigorously conducted.

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Description

Modern Biostatistical Methods for Evidence-Based Global Health Research (Emerging Topics in Statistics and Biostatistics)

By Ding-Geng (Din) Chen (Editor), Samuel O. M. Manda (Editor), Tobias F. Chirwa (Editor)

Key Topics Covered: The volume is divided into five main parts, each addressing critical areas of biostatistics in global health:
1. Data Harmonization and Analysis: Techniques for integrating and analyzing data from diverse sources.
2. Systematic Review and Statistical Meta-Analysis: Methods for synthesizing research findings and performing meta-analyses.
3. Spatial-Temporal Modeling and Disease Mapping: Approaches for modeling disease distribution and trends over time and space.
4. Bayesian Statistical Modeling: Use of Bayesian methods for probabilistic modeling in health research.
5. Statistical Methods for Longitudinal or Survival Data: Techniques for analyzing data collected over time or focusing on survival analysis.

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