Description

Book Synopsis

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 estimation
  • First book to synthesize research in this field in a unified statistical framework
  • Covers classical approaches, and builds to more modern computational techniques

    • Table of Contents

    1. Basic Concepts. 2. Overall Estimation of Health Disparities. 3. Domain-specific Estimates. 4. Causality, Moderation and Meditation. 5. Machine Learning Based Approaches to Disparity Estimation. 6. Health Disparity Estimation Under a Precision Medicine Paradigm. 7. Extended Topics.

Statistical Methods in Health Disparity Research

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    A Hardback by J. Sunil Rao

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      Publisher: Taylor & Francis Ltd
      Publication Date: Publication Date: 7/11/2023 12:00:00 AM
      ISBN13: 9780367635121, 978-0367635121
      ISBN10: 0367635127
      Also in:
      Epidemiology and Medical statistics Health systems and services Social and ethical issues

      Description

      Book Synopsis

      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 estimation
      • First book to synthesize research in this field in a unified statistical framework
      • Covers classical approaches, and builds to more modern computational techniques

        • Table of Contents

        1. Basic Concepts. 2. Overall Estimation of Health Disparities. 3. Domain-specific Estimates. 4. Causality, Moderation and Meditation. 5. Machine Learning Based Approaches to Disparity Estimation. 6. Health Disparity Estimation Under a Precision Medicine Paradigm. 7. Extended Topics.

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