Statistical Methods in Health Disparity Research

图书简介

A health disparity refers to a higher burden of illness, injury, disability, or mortality experienced by one group relative to others attributable to multiple factors including socioeconomic status, environmental factors, insufficient access to health care, individual risk factors, and behaviors and inequalities in education. These disparities may be due to many factors including age, income, and race. Statistical Methods in Health Disparity Research will focus on their estimation, ranging from classical approaches including the quantification of a disparity, to more formal modeling, to modern approaches involving more flexible computational approaches.Features:Presents an overview of methods and applications of health disparity estimationFirst book to synthesize research in this field in a unified statistical frameworkCovers classical approaches, and builds to more modern computational techniquesIncludes many worked examples and case studies using real dataDiscusses available software for estimationThe book is designed primarily for researchers and graduate students in biostatistics, data science, and computer science. It will also be useful to many quantitative modelers in genetics, biology, sociology, and epidemiology.

Foreword Preface 1 Basic Concepts 1.1 What is a health disparity 1.2 A brief historical perspective 1.3 Some examples 1.4 Determinants of Health 1.4.1 Biology and genetics 1.4.2 Individual behavior 1.4.3 Health services 1.4.4 Social determinants of health 1.4.5 (Health) policies The challenging issue of race Racial segregation as a social determinant of health Racism, segregation, and inequality Role of data visualization in health disparities research A note on notation adopted in this book Overall Estimation of Health Disparities Data and Measurement Disparity indices Total disparity indices Disparity indices measuring differences between groups Disparity indices from complex surveys Randomized experiments: an idealized estimate of disparity Model-based estimation: adjusting for confounders Regression approach Model-assisted survey regression Peters-Belson approach Peters-Belson approach for complex survey 2.4.2.2 Peters- Belson approach for clustered data 2.4.3 Disparity drivers 2.4.3.1 Disparity drivers for complex survey data Matching and propensity scoring Discrete outcomes Binary outcomes Nominal and ordinal outcomes Poisson regression and log-linear models

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Statistical Methods in Health Disparity Research（Chapman ） 健康差异研究中的统计方法 医学生物化学

Statistical Methods in Health Disparity Research（Chapman ）

健康差异研究中的统计方法
医学生物化学