Edited
By José R. Zubizaretta, Elizabeth A. Stuart, Dylan S. Small, Paul R. Rosenbaum
March 22, 2023
An observational study infers the effects caused by a treatment, policy, program, intervention, or exposure in a context in which randomized experimentation is unethical or impractical. One task in an observational study is to adjust for visible pretreatment differences between the treated ...
Edited
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, ...
Edited
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, ...
Edited
By Mahlet G. Tadesse, Marina Vannucci
December 20, 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 ...
Edited
By Xinping Cui, Thorsten Dickhaus, Ying Ding, Jason C. Hsu
November 16, 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. ...
Edited
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 ...
Edited
By KyungMann Kim, Frank Bretz, Ying Kuen K. Cheung, Lisa V. Hampson
August 30, 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 ...
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By Leonhard Held, Niel Hens, Philip O'Neill, Jacco Wallinga
November 04, 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 ...
Edited
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) ...
Edited
By John O'Quigley, Alexia Iasonos, Björn Bornkamp
May 22, 2017
Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials gives a thorough presentation of state-of-the-art methods for early phase clinical trials. The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of ...
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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 ...
Edited
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 ...
