Data Analysis with Competing Risks and Intermediate States - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Analysis with Competing Risks and Intermediate States write by Ronald B. Geskus. This book was released on 2015-07-14. Data Analysis with Competing Risks and Intermediate States available in PDF, EPUB and Kindle. Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results.After introducing example studies from the biomedical and
Models for Multi-State Survival Data
Models for Multi-State Survival Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Models for Multi-State Survival Data write by Per Kragh Andersen. This book was released on 2023-10-11. Models for Multi-State Survival Data available in PDF, EPUB and Kindle. 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 can be found on the book’s webpage.
Competing Risks and Multistate Models with R
Competing Risks and Multistate Models with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Competing Risks and Multistate Models with R write by Jan Beyersmann. This book was released on 2011-11-18. Competing Risks and Multistate Models with R available in PDF, EPUB and Kindle. This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.
Principles and Methods for Data Science
Principles and Methods for Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Principles and Methods for Data Science write by . This book was released on 2020-05-28. Principles and Methods for Data Science available in PDF, EPUB and Kindle. Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Statistics series - Updated release includes the latest information on Principles and Methods for Data Science
Absolute Risk
Absolute Risk - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Absolute Risk write by Ruth M. Pfeiffer. This book was released on 2017-08-10. Absolute Risk available in PDF, EPUB and Kindle. Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow statisticians, epidemiologists, and clinicians to build, test, and apply models of absolute risk. Features: Provides theoretical basis for modeling absolute risk, including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate models Provides details on statistical inference for the various sampling designs Discusses criteria for evaluating risk models and comparing risk models, including both general criteria and problem-specific expected losses in well-defined clinical and public health applications Describes many applications encompassing both disease prevention and prognosis, and ranging from counseling individual patients, to clinical decision making, to assessing the impact of risk-based public health strategies Discusses model updating, family-based designs, dynamic projections, and other topics Ruth M. Pfeiffer is a mathematical statistician and Fellow of the American Statistical Association, with interests in risk modeling, dimension reduction, and applications in epidemiology. She developed absolute risk models for breast cancer, colon cancer, melanoma, and second primary thyroid cancer following a childhood cancer diagnosis. Mitchell H. Gail developed the widely used "Gail model" for projecting the absolute risk of invasive breast cancer. He is a medical statistician with interests in statistical methods and applications in epidemiology and molecular medicine. He is a member of the National Academy of Medicine and former President of the American Statistical Association. Both are Senior Investigators in the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.
