Modern Methods for Epidemiology

  • Yu-Kang Tu
  • Darren C. Greenwood

Table of contents

  1. Front Matter
    Pages i-xii
  2. Graham R. Law, Rosie Green, George T. H. Ellison
    Pages 1-13
  3. James R. Carpenter, Harvey Goldstein, Michael G. Kenward
    Pages 15-31
  4. Darren C. Greenwood
    Pages 33-55
  5. Graham R. Law, Paul D. Baxter, Mark S. Gilthorpe
    Pages 57-71
  6. Andrew Blance
    Pages 73-91
  7. Mark S. Gilthorpe, Morten Frydenberg, Yaping Cheng, Vibeke Baelum
    Pages 93-115
  8. Wendy Harrison, Robert M. West, Amy Downing, Mark S. Gilthorpe
    Pages 117-140
  9. Richard G. Feltbower, Samuel O. M. Manda
    Pages 141-155
  10. Samuel O. M. Manda, Richard G. Feltbower, Mark S. Gilthorpe
    Pages 157-172
  11. Darren C. Greenwood
    Pages 173-189
  12. Yu-Kang Tu, Francesco D’Auito
    Pages 205-221
  13. Kate Tilling, Jonathan A. C. Sterne, Vanessa Didelez
    Pages 243-260
  14. Robert M. West
    Pages 261-278
  15. Robert M. West
    Pages 279-290
  16. Mark S. Gilthorpe, David G. Clayton
    Pages 291-311
  17. Back Matter
    Pages 313-314

About this book


Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.


Bayesian analysis Biostatistics Directed acyclic graphs Epidemiological methods Latent variable modelling

Editors and affiliations

  • Yu-Kang Tu
    • 1
  • Darren C. Greenwood
    • 2
  1. 1.Leeds Institute of Genetics, University of LeedsDivision of BiostatisticsLeedsUnited Kingdom
  2. 2.Leeds Institute of Genetics, University of LeedsDivision of BiostatisticsLeedsUnited Kingdom

Bibliographic information