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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Order before 4pm today for delivery by Fri 13 Mar 2026.

A Hardback by J. Sunil Rao

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    View other formats and editions of Statistical Methods in Health Disparity Research by J. Sunil Rao

    Publisher: Taylor & Francis Ltd
    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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