The objective of the series is to provide high-quality volumes covering the state-of-the-art in the theory and applications of statistical methodology. The books in the series are thoroughly-edited and present comprehensive, coherent and unified summaries of specific methodological topics from statistics. The chapters are written by the leading researchers in the field, and present a good balance of theory and application through a synthesis of the key methodological developments and examples and case studies using real data.
The scope of the series is wide, covering topics of statistical methodology that are well developed and find application in a range of scientific disciplines. The volumes are primarily of interest to researchers and graduate students from statistics and biostatistics, but also appeal to scientists from fields where the methodology is applied to real problems, including medical research, epidemiology and public health, engineering, biological science, environmental science and the social sciences.
Please contact us if you have an idea for a book for the series.
Handbook of Forensic Statistics
Handbook of Meta-Analysis
Handbook of Bayesian Variable Selection
Handbook of Multiple Comparisons
Handbook of Measurement Error Models
Handbook of Infectious Disease Data Analysis
Handbook of Mixture Analysis
Handbook of Graphical Models
Handbook of Approximate Bayesian Computation
By David L. Banks, Karen Kafadar, David H. Kaye, Maria Tackett
May 30, 2022
Handbook of Forensic Statistics is a collection of chapters by leading authorities in forensic statistics. Written for statisticians, scientists, and legal professionals having a broad range of statistical expertise, it summarizes and compares basic methods of statistical inference (frequentist, ...
By Christopher H. Schmid, Theo Stijnen, Ian White
March 27, 2022
Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the last 25 years as the need for a robust evidence base has become clear in many scientific areas, including medicine and health, ...
By Mahlet G. Tadesse, Marina Vannucci
December 21, 2021
Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the ...
By Xinping Cui, Thorsten Dickhaus, Ying Ding, Jason C. Hsu
November 18, 2021
Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems. ...
By Grace Y. Yi, Aurore Delaigle, Paul Gustafson
October 18, 2021
Measurement error arises ubiquitously in applications and has been of long-standing concern in a variety of fields, including medical research, epidemiological studies, economics, environmental studies, and survey research. While several research monographs are available to summarize methods and ...
By KyungMann Kim, Frank Bretz, Ying Kuen K. Cheung, Lisa V. Hampson
August 23, 2021
Statistical concepts provide scientific framework in experimental studies, including randomized controlled trials. In order to design, monitor, analyze and draw conclusions scientifically from such clinical trials, clinical investigators and statisticians should have a firm grasp of the requisite ...
By Leonhard Held, Niel Hens, Philip D O'Neill, Jacco Wallinga
October 25, 2019
Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis ...
By Jim Albert, Mark E. Glickman, Tim B. Swartz, Ruud H. Koning
September 11, 2019
This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer) ...
By Alan E. Gelfand, Montserrat Fuentes, Jennifer A. Hoeting, Richard Lyttleton Smith
February 11, 2019
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in ...
By Sylvia Fruhwirth-Schnatter, Gilles Celeux, Christian P. Robert
January 07, 2019
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and ...
By Marloes Maathuis, Mathias Drton, Steffen Lauritzen, Martin Wainwright
November 27, 2018
A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed ...
By Scott A. Sisson, Yanan Fan, Mark Beaumont
August 10, 2018
As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ...