Ties Between Event Times and Covariate Change Times in Cox Models
Author | : Xin Xin |
Publisher | : |
Total Pages | : |
Release | : 2014 |
Genre | : |
ISBN | : |
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Author | : Xin Xin |
Publisher | : |
Total Pages | : |
Release | : 2014 |
Genre | : |
ISBN | : |
Author | : Xin Xin |
Publisher | : |
Total Pages | : |
Release | : 2011 |
Genre | : |
ISBN | : |
Author | : Terry M. Therneau |
Publisher | : Springer Science & Business Media |
Total Pages | : 356 |
Release | : 2013-11-11 |
Genre | : Mathematics |
ISBN | : 1475732945 |
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.
Author | : Luc Duchateau |
Publisher | : Springer Science & Business Media |
Total Pages | : 329 |
Release | : 2007-10-23 |
Genre | : Mathematics |
ISBN | : 038772835X |
Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.
Author | : Eric Leip |
Publisher | : |
Total Pages | : 396 |
Release | : 2005 |
Genre | : |
ISBN | : |
Abstract: This dissertation adapts a method for applying the Cox proportional hazards model when the change time of a binary time-varying covariate is interval censored. The bivariate case was motivated by the relationship between cardiovascular disease events and first occurrence of hypertension in males at the Framingham Heart Study. The Heart Study has regularly scheduled examinations every two to four years depending on the cohort. The change time from non-hypertensive to hypertensive state is known only to lie between the last non-hypertensive exam and the first hypertensive exam. A time-dependent Cox model uses the timing of the covariate change relative to event times to assess the effect of the covariate with the event of interest. The hypertension change time is unknown in our data. Our methodology employs the same Monte Carlo EM algorithm as does the original method by Goggins in Biometrics (1999), but introduces a new sampling technique that replaces the Gibbs sampler used in the original. The differences in computing time are analyzed. Along with the new sampling technique, the original method is adapted to allow for two covariates, a multivariable model. The relationship between cardiovascular disease with first occurrences of both hypertension and diabetes prompted this extension. The change times of these two binary time-varying covariates are interval censored, since both hypertension and diabetes statuses are evaluated at each attended examination. Simulations are run to test the validity of our new approach.
Author | : John D. Kalbfleisch |
Publisher | : John Wiley & Sons |
Total Pages | : 462 |
Release | : 2011-01-25 |
Genre | : Mathematics |
ISBN | : 1118031237 |
Contains additional discussion and examples on left truncationas well as material on more general censoring and truncationpatterns. Introduces the martingale and counting process formulation swillbe in a new chapter. Develops multivariate failure time data in a separate chapterand extends the material on Markov and semi Markovformulations. Presents new examples and applications of data analysis.
Author | : Melinda Mills |
Publisher | : SAGE |
Total Pages | : 301 |
Release | : 2011-01-19 |
Genre | : Social Science |
ISBN | : 1848601026 |
This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.
Author | : Jan Beyersmann |
Publisher | : Springer Science & Business Media |
Total Pages | : 249 |
Release | : 2011-11-18 |
Genre | : Mathematics |
ISBN | : 1461420350 |
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.
Author | : John P. Klein |
Publisher | : Springer Science & Business Media |
Total Pages | : 508 |
Release | : 2013-06-29 |
Genre | : Medical |
ISBN | : 1475727283 |
Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.
Author | : Judith D. Singer |
Publisher | : Oxford University Press |
Total Pages | : 665 |
Release | : 2003-03-27 |
Genre | : Mathematics |
ISBN | : 0199882401 |
Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: BL Downloadable data sets BL Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more BL Additional material for data analysis