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"Statistical Methods in Health Disparity Research" by J. Sunil Rao is a comprehensive book that explores statistical methods for estimating health disparities. The book covers various approaches, including non-model and linear-based models, as well as the application of machine learning. It emphasizes the importance of validating findings and discusses the advantages and limitations of each method. The book is divided into seven chapters, which cover topics such as basic concepts of health disparities, estimation of health disparities, domain-specific estimates, causality, moderation, and mediation, machine learning-based approaches, health disparity estimation under a precision medicine paradigm, and extended topics. While the book has some structural inconsistencies, it offers a diverse range of topics and provides in-depth explanations of complex concepts. It is recommended for students, professionals in public health or health policy, researchers, and practitioners working with vulnerable populations. [Extracted from the article]