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"Parametric Mixture Models for Survival Data Analysis" is a comprehensive book authored by R.Uma Maheswari, focused on the analysis of heterogeneous survival data using parametric mixture models. The book is designed to provide readers with a deep understanding of the latest research and developments in the field of survival analysis using mixture models. The book begins by introducing the fundamental concepts of survival analysis, including censoring, truncation, and hazard functions. It then delves into the theory of parametric mixture models and their applications in analyzing survival data…mehr

Produktbeschreibung
"Parametric Mixture Models for Survival Data Analysis" is a comprehensive book authored by R.Uma Maheswari, focused on the analysis of heterogeneous survival data using parametric mixture models. The book is designed to provide readers with a deep understanding of the latest research and developments in the field of survival analysis using mixture models. The book begins by introducing the fundamental concepts of survival analysis, including censoring, truncation, and hazard functions. It then delves into the theory of parametric mixture models and their applications in analyzing survival data from different populations with varying characteristics. The author presents various types of mixture models, including the homogeneous model, the mixture cure model, the frailty model, and the multistate model, among others. Each model is discussed in detail, including its assumptions, implementation, and interpretation. The book also covers advanced topics such as the estimation of the parameters of the mixture model, the selection of the appropriate number of components, and the evaluation of model fit. Overall, "Parametric Mixture Models for Survival Data Analysis" is an essential resource for researchers and practitioners in the field of survival analysis. It provides a comprehensive overview of the theory and practice of parametric mixture models and their applications in analyzing heterogeneous survival data, making it an indispensable reference for anyone interested in the analysis of survival data from diverse populations.