Essential Statistical Skills for Public Health Practice: With R

Description

Quantitative literacy has become an indispensable skill for researchers, clinicians, policy analysts, and students across the health and social sciences. Yet a persistent gap exists between statistical textbooks that assume prior programming expertise and those that sacrifice rigour in the name of accessibility. This book is designed to occupy exactly that middle ground — rigorous enough for... Read more

Quantitative literacy has become an indispensable skill for researchers, clinicians, policy analysts, and students across the health and social sciences. Yet a persistent gap exists between statistical textbooks that assume prior programming expertise and those that sacrifice rigour in the name of accessibility. This book is designed to occupy exactly that middle ground — rigorous enough for postgraduate study and professional research, yet accessible enough for anyone encountering R for the first time.

Using R, the world's leading open-source environment for statistical computing, this book guides readers through a coherent analytical workflow from raw data to publication-ready results. Grounded in real and realistic public health datasets, every concept is illustrated with executable R code that readers can replicate, adapt, and build upon. The emphasis throughout is on practical application, reproducible analysis, and clear interpretation of results — not just on running procedures.

Key features:

Comprehensive coverage of data management using the tidyverse suite, including importing, cleaning, reshaping, and handling missing data
Step-by-step data visualisation using ggplot2, covering bar charts, violin plots, histograms, and combination plots for categorical and numerical variables
Descriptive statistics including measures of central tendency and dispersion, with visual interpretation
Hypothesis testing frameworks with decision flowcharts, covering matched and unmatched two-group and multi-group tests, including ANOVA and non-parametric alternatives
Survival analysis using Kaplan-Meier curves and Cox proportional hazards models
Regression modelling including OLS linear regression, logistic regression, and probit regression with model evaluation techniques
Complete meta-analysis workflow across two dedicated chapters, including forest plots, subgroup analyses, meta-regiression, publication bias assessment, and Bayesian meta-analysis
Dimension reduction and unsupervised learning through Principal Component Analysis, k-means clustering, hierarchical clustering, and DBSCAN

Written by an international team of public health researchers, biostatisticians, and data scientists, this book is an essential companion for MSc and PhD students, academic researchers, and public health practitioners who wish to develop confident, reproducible analytical skills in R.

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Dedication Acknowledgements Foreword Preface Chapter 1: Introduction — Data Management in R Chapter 2: Plotting Chapter 3: Plotting of Categorical and Numerical Variables Chapter 4: Measures of Central Tendency and Dispersion in R Chapter 5: Hypothesis Testing Chapter 6: Tests of Significance for Matched Data in Two Groups Chapter 7: Tests of Significance for Unmatched Data in Two Groups Chapter 8: Tests of Significance for Matched Data in Multiple Groups Chapter 9: Tests of Significance for Unmatched Data in Multiple Groups Chapter 10: Two-Way ANOVA Chapter 11: Survival Analysis Chapter 12: Correlation Analysis in R Chapter 13: Regression Analysis — OLS Method in R Chapter 14: Predicting Binary Outcomes — Logistic and Probit Regression Chapter 15: How to Perform a Meta-Analysis Chapter 16: How to Present a Meta-Analysis Chapter 17: Principal Component Analysis in R Chapter 18: Clustering

Author(s)

Biography

Dr. Russell Kabir is Associate Professor of Public Health and Biostatistics at Anglia Ruskin University, Cambridge and Chelmsford, UK, where he serves as Course Director for the MSc Public Health and Community Wellbeing programme. He holds fellowships from the Royal Statistical Society and the Higher Education Academy. His research spans intimate partner violence, climate-health intersections, applied biostatistics, and machine learning applications in public health, with over 200 publications and an h-index of 40. He has led and contributed to international research collaborations across South Asia, the Middle East, and Africa, and holds a background in dental surgery from the University of Dhaka alongside his public health career.

Dr. Ali Davod Parsa is currently working as an Associate Professor of Health Economics, Policy & Management, at the School of Allied Health - Faculty of Health, Education, Medicine and Social Care, Anglia Ruskin University in Cambridge (UK). He has an established, proven track record of success at a very senior level of leadership, collaborative research, and teaching excellence at undergraduate, postgraduate and doctoral levels and has held a series of high-profile governmental appointments in the Ministry of Health and Medical Education in Iran before joining to the UK-HEIs.Dr Parsa first graduated as a qualified GP from the School of Medicine- University of Zanjan, Medical Sciences and Health Services, Iran in 1994.

Dr. Muhammad Aaqib Shamim has an interest in integration of pharmacoeconomics, evidence synthesis, and clinical trials including live interactive dashboards, and has contributed to national guideline development projects. He focuses on robust research methodology, and has published letters to editors as critiques in journals like New England Journal of Medicine, The Lancet Microbe, and The Lancet Oncology. In addition to research, he is actively involved in capacity building through workshops, mentorship, and tutorial publications.

Dr. Krishna Tiwari completed her medical training and subsequently gained clinical experience across diverse healthcare settings. She has authored numerous peer-reviewed publications and presented her research at international scientific conferences. Following formal training and research experience in pharmacology, she is currently expanding her work into topical preparations.

Dr. Aswath Karunakaran is a public health consultant, medical doctor, and data analyst with over seven years of experience in monitoring, evaluation, and learning, health systems strengthening, implementation research, and disease surveillance. He has worked with leading national and international organizations, including PATH, WHO, The Union, and NLR India, supporting public health programs, clinical research, and evidence-informed decision-making. His interests lie in applying epidemiology, data science, and advanced analytical methods.

Dr. Vikas Kumar Tiwari is an Indian physician-scientist whose work neuroscience, and computational research. After earning his MBBS with distinction from Gandhi Medical College, Bhopal, and completing his MD in Physiology at AIIMS New Delhi, he is currently pursuing a PhD at Tohoku University, Japan, under the Neuroglobal Researcher Fellowship Program. His research focuses on the neurophysiological mechanisms of transcranial magnetic stimulation, while his broader contributions span neuroscience, medical education, scientific communication, and the application of programming and data analytics in healthcare.

Essential Statistical Skills for Public Health Practice With R

Description

Table of Contents

Author(s)

Biography

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