Statistical Methods in Health Disparity Research

Health disparities are differences in health outcomes between groups of people due to various factors, such as socioeconomic status, environmental factors, and access to healthcare. This book provides an overview of methods and applications for estimating health disparities, including classical approaches and modern computational techniques. It is designed for researchers and graduate students in biostatistics, data science, and computer science, as well as quantitative modelers in other fields.

Format: Hardback
Length: 280 pages
Publication date: 11 July 2023
Publisher: Taylor & Francis Ltd

A health disparity refers to a significant difference in the burden of illness, injury, disability, or mortality experienced by one group compared to others, which can be attributed to a multitude of factors such as socioeconomic status, environmental factors, limited access to healthcare, individual risk factors, and behaviors. These disparities can arise from various factors, including age, income, and race.

In order to address and understand these health disparities, statistical methods play a crucial role in research. This book aims to provide a comprehensive overview of the estimation of health disparities, encompassing a range of approaches, from classical methods that quantify disparities to more formal modeling techniques and modern computational approaches.

The book begins by introducing the fundamental concepts and theories related to health disparities estimation. It then delves into the various methods and applications of health disparity estimation, including both classical approaches and more modern computational techniques. Classical approaches involve quantifying disparities using measures such as absolute and relative differences, while more modern computational techniques involve using advanced statistical models and machine learning algorithms.

Throughout the book, numerous worked examples and case studies are provided, using real data to illustrate the practical application of the methods discussed. These examples help to demonstrate the strengths and limitations of different estimation approaches and provide insights into how they can be used to inform policy and practice.

In addition to its coverage of estimation methods, the book also discusses the available software for health disparity estimation. This includes both free and commercial software, which can be valuable tools for researchers and practitioners alike. The book is designed primarily for researchers and graduate students in biostatistics, data science, and computer science, as well as quantitative modelers in genetics, biology, sociology, and epidemiology. It provides a comprehensive and up-to-date introduction to the field of health disparity estimation, making it an essential resource for anyone interested in this area of research.

Weight: 624g
Dimension: 162 x 241 x 20 (mm)
ISBN-13: 9780367635121