The primary objectives of the series are to provide useful reference books for researchers and scientists in academia, industry, and government, and also to offer textbooks for undergraduate and graduate courses in the areas of biostatistics and bioinformatics. The book series will provide comprehensive and unified presentations of statistical designs and analyses of important applications in biostatistics and bioinformatics, such as those in biological and biomedical research.
The scope of the series is wide, including applications of statistical methodology in biology, epidemiology, genetics, pharmaceutical science and clinical trials, public health, and medicine. The series is committed to providing easy to understand, state-of-the-art references and textbooks. In each volume, statistical concepts and methodologies will be illustrated through real world examples whenever possible.
Please contact us if you have an idea for a book for the series.
By Jun Ma, Malcolm Hudson, Annabel Webb
October 01, 2024
Many conventional survival analysis methods, such as the Kaplan-Meier method for survival function estimation and the partial likelihood method for Cox model regression coefficients estimation, were developed under the assumption that survival times are subject to right censoring only. However, in ...
By Hongjie Liu
August 05, 2024
Association Models in Epidemiology: Study Design, Modeling Strategies, and Analytic Methods is written by an epidemiologist for graduate students, researchers, and practitioners who will use regression techniques to analyze data. It focuses on association models rather than prediction models. The ...
By Yinglin Xia, Jun Sun
July 22, 2024
This unique book officially defines microbiome statistics as a specific new field of statistics and addresses the statistical analysis of correlation, association, interaction, and composition in microbiome research. It also defines the study of the microbiome as a hypothesis-driven ...
By Yixin Fang
June 24, 2024
Causal Inference in Pharmaceutical Statistics introduces the basic concepts and fundamental methods of causal inference relevant to pharmaceutical statistics. This book covers causal thinking for different types of commonly used study designs in the pharmaceutical industry, including but not ...
By Peihua Qiu
June 18, 2024
Disease screening and disease surveillance (DSDS) constitute two critical areas in public health, each presenting distinctive challenges primarily due to their sequential decision-making nature and complex data structures. Statistical Methods for Dynamic Disease Screening and Spatio-Temporal ...
Edited
By Wei Zhang, Fangrong Yan, Feng Chen, Shein-Chung Chow
May 27, 2024
Advanced Statistics in Regulatory Critical Clinical Initiatives is focused on the critical clinical initiatives introduced by the 21st Century Cure Act passed by the United States Congress in December 2016. The book covers everything from the outline of the initiatives to analysis on the effect on ...
By Qingzhao Yu, Bin Li
May 27, 2024
Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers. ...
By Michael A. Proschan
May 27, 2024
Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and ...
Edited
By Avery McIntosh, Oleksandr Sverdlov
May 23, 2024
Cell and gene therapies have become the third major drug modality in pharmaceutical medicine of the 21st century after low molecular weight and antibody drugs. The gene therapy (GTx) field is rapidly advancing, and yet there are still fundamental scientific questions that remain to be answered. ...
By Peter F. Thall
May 07, 2024
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical ...
Edited
By Anna Heath, Natalia Kunst, Christopher Jackson
February 08, 2024
Value of Information for Healthcare Decision-Making introduces the concept of Value of Information (VOI) use in health policy decision-making to determine the sensitivity of decisions to assumptions, and to prioritise and design future research. These methods, and their use in cost-effectiveness ...
By Dongfeng Wu
February 06, 2024
Cancer screening has been carried out for six decades – however, there are many unsolved problems: how to estimate key parameters involved in screenings, such as sensitivity, the time duration in the preclinical state (i.e., sojourn time), and time duration in the disease-free state; how to ...