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Modeling Survival Data: Extending the Cox Model
This book is for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyze multiple/correlated event data using marginal and random effects. The focus is on actual data examples, the analysis and interpretation of results, and computation. The book shows how these new methods can be implemented in SAS and S-Plus, including computer code, worked examples, and data sets.
Joint Replacement Arthroplasty
Thoroughly updated and expanded into two separate volumes, the Fourth Edition of Joint Replacement Arthroplasty provides comprehensive coverage of primary and revision arthroplasty procedures for the upper and lower extremities. This definitive text is written by world-renowned experts from the Mayo Clinic and other leading institutions and includes data from the Mayo Clinic's extensive patient records from 1969 through 2009. This first volume covers the elbow and shoulder and includes online access to 30 chapters on the basic science that supports joint replacement. Sections on each joint cover anatomy and surgical approaches, navigation, biomechanics, prosthesis design, primary arthroplasty, complications, revision arthroplasty, and alternative procedures. This edition includes more practical advice on diagnosing and managing the underlying problems and more step-by-step operative guidelines. The companion website allows you to search across both Volume 1 and Volume 2, which covers the hip, knee, and ankle. The online-only basic science chapters provide thorough coverage of materials used for joint replacements and management of patients with various medical conditions.
Modern Applied Statistics with S
A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.
Proceedings of the First Seattle Symposium in Biostatistics: Survival Analysis
The papers in this volume discuss important methodological advances in several important areas, including multivariate failure time data and interval censored data. The book will be an indispensable reference for researchers and practitioners in biostatistics, medical research, and the health sciences.
Statistical Application Development with R and Python
Software Implementation Illustrated with R and Python About This Book Learn the nature of data through software which takes the preliminary concepts right away using R and Python. Understand data modeling and visualization to perform efficient statistical analysis with this guide. Get well versed with techniques such as regression, clustering, classification, support vector machines and much more to learn the fundamentals of modern statistics. Who This Book Is For If you want to have a brief understanding of the nature of data and perform advanced statistical analysis using both R and Python, then this book is what you need. No prior knowledge is required. Aspiring data scientist, R users tr...
Statistical Methods in Epilepsy
Epilepsy research promises new treatments and insights into brain function, but statistics and machine learning are paramount for extracting meaning from data and enabling discovery. Statistical Methods in Epilepsy provides a comprehensive introduction to statistical methods used in epilepsy research. Written in a clear, accessible style by leading authorities, this textbook demystifies introductory and advanced statistical methods, providing a practical roadmap that will be invaluable for learners and experts alike. Topics include a primer on version control and coding, pre-processing of imaging and electrophysiological data, hypothesis testing, generalized linear models, survival analysis,...
ECAI 2010
LC copy bound in 2 v.: v. 1, p. 1-509; v. 2, p. [509]-1153.
Practical Statistics for Data Scientists
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap...
Novel Diagnostic and Therapeutic Strategies in the Management of Cerebral Gliomas
Cerebral gliomas account for 45% of all primary central nervous system (CNS) tumors. The median survival after the initial diagnosis of glioblastoma (GBM) is only 15 months, and less than 10% of patients survive three years post-diagnosis. Surgical treatment followed by adjuvant therapies such as radiotherapy and chemotherapy represents the classical strategy in glioma management. The revised WHO 2016 classification now distinguishes the oligodendrogliomas with 1p19q codeletion and IDH mutation from the astrocytomas with or without IDH mutations, thereby creating homogenous and pathologically distinct subgroups. While the status of gene expression and mutations define components of GBM subtypes, it was also found that response to therapies was different for each subtype, suggesting that personalized treatment based on genomic alterations could lead to a more favorable outcome for this disease.
Bayesian Survival Analysis
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. It presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all from the health sciences, including cancer, AIDS, and the environment.
