Description

Book Synopsis
Advanced Statistics for Health Research provides a rigorous geometric understanding of models used in the analysis of health data, including linear and non-linear regression models, and supervised machine learning models. Models drawn from the health literature include: ordinary least squares, two-stage least squares, probits, logits, Cox regressions, duration modeling, quantile regression and random forest regression. Causal inference techniques from the health literature are presented including randomization, matching and propensity score matching, differences-in-differences, instrumental variables, regression discontinuity, and fixed effects analysis. Codes for the respective statistical techniques presented are given for STATA, SAS and R.

Advanced Statistics For Health Research

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A Hardback by Richard J Butler, Matthew J Butler, Barbara L Wilson

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    View other formats and editions of Advanced Statistics For Health Research by Richard J Butler

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 12/05/2023
    ISBN13: 9789811262302, 978-9811262302
    ISBN10: 9811262306
    Also in:
    Health economics

    Description

    Book Synopsis
    Advanced Statistics for Health Research provides a rigorous geometric understanding of models used in the analysis of health data, including linear and non-linear regression models, and supervised machine learning models. Models drawn from the health literature include: ordinary least squares, two-stage least squares, probits, logits, Cox regressions, duration modeling, quantile regression and random forest regression. Causal inference techniques from the health literature are presented including randomization, matching and propensity score matching, differences-in-differences, instrumental variables, regression discontinuity, and fixed effects analysis. Codes for the respective statistical techniques presented are given for STATA, SAS and R.

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