{ "item_title" : "Models for Multi-State Survival Data", "item_author" : [" Per Kragh Andersen", "Henrik Ravn "], "item_description" : "Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject.Key Features: Intensity-based and marginal models. Survival data, competing risks, illness-death models, recurrent events. Includes a full chapter on pseudo-values. Intuitive introductions and mathematical details. Practical examples of event history data. Exercises. Software code in R and SAS and the data used in the book, as well as solutions to the exercises, can be found on the book's webpage: https: //multi-state-book.github.io/companion. ", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/0/36/714/002/0367140020_b.jpg", "price_data" : { "retail_price" : "115.99", "online_price" : "115.99", "our_price" : "115.99", "club_price" : "115.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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