Methods of Clinical Epidemiology (Springer Series on Epidemiology and Public Health)

“Methods of Clinical Epidemiology” serves as a text on methods useful to clinical researchers. It provides a clear introduction to the common research methodology specific to clinical research for both students and researchers. This book sets out to fill the gap left by texts that concentrate on public health epidemiology and focuses on what is not covered well in such texts. The four sections cover methods that have not previously been brought together in one text and serves as a second level textbook of clinical epidemiology methodology. This book will be of use to postgraduate students in clinical epidemiology as well as clinical researchers at the start of their careers.

Suhail Doi is an Associate Professor of Clinical Epidemiology at the University of Queensland. He is involved in teaching, student supervision, curriculum development and research. He has published widely and his interest lies in research that addresses unanswered questions in patient care as well as questions related to methods of research design and analysis used in Medicine. Thus his research focuses on patient care topics such as epidemiology, prognosis and treatments of disease as well as methodology especially that related to meta-analysis. He is the co-author of the Doi–Thalib method for meta-analysis which was introduced in 2008 as an alternative to the random effects model.

Gail Williams is Professor of International Health Statistics at the University of Queensland. She has had long involvement in curriculum development and teaching in graduate programs in biostatistics and epidemiology, as well as consulting in clinical medicine and public health. Her specific areas of expertise include design and analysis of longitudinal studies, clinical and field intervention trials, survey design, and mathematical modelling. The focus of her applied research has been maternal and child health, a range of infectious diseases, and skin cancer. Her methodological areas of interest lie in statistical and mathematical modelling and approaches to dealing with attrition in longitudinal studies.