Advanced Statistics for Health Research: A Comprehensive Guide

Authors: Richard J Butler, Matthew J Butler, Barbara L Wilson

Publication Date: May 13, 2023

Pages: 404

ISBN-10: 9811262306

ISBN-13: 978-9811262302

Language: English

Format: Hardcover

Publisher: World Scientific Publishing Company

Summary: 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.

Key Features:– Comprehensive guide to statistical models and techniques in health research- Includes linear and non-linear regression models, supervised machine learning models, and causal inference techniques- Codes provided for STATA, SAS, and R- Ideal for researchers, students, and professionals in the field of health research

Table of Contents:– Introduction to Health Data Analysis- Linear Regression Models- Non-Linear Regression Models- Supervised Machine Learning Models- Causal Inference Techniques- Applications in Health Research- Conclusion

Target Audience: Researchers, students, and professionals in the field of health research