Download or read book Inference in the Cox Proportional Hazards Model with Missing Covariate Data written by Marian Glynis Pugh and published by . This book was released on 1993 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Inference for the Proportional Hazards Model written by Ronghui Xu and published by . This book was released on 1996 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Post selection Inference in Cox Proportional Hazards Models written by Carla Louw and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Variable selection causes the distributions of parameter estimators to be unknown and difficult to determine. To do inference after selection, conditional distributions for parameter estimators given the selected model are needed. Taylor and Tibshirani (2018) call this post-selection inference and describe an estimator of regression parameters along with the corresponding conditional distribution, making post-selection inference possible. The Polyhedral Lemma (Lee et al., 2016) is used to determine the conditional distribution of this estimator given the model selected - a truncated normal distribution. We implement Taylor and Tibshirani's (2018) method in the Cox Proportional Hazards Regression setting and do a Monte Carlo study. The results are analyzed. The method controls the level of tests and coverage of confidence intervals well - much better than unadjusted Cox Proportional Hazards techniques. Numerical difficulties in the Cox Proportional Hazards software are identified and addressed in the post-selection inference context.
Download or read book Robust Inference for the Cox s Proportional Hazards Model with Frailties written by Muhammad Jalaluddin and published by . This book was released on 1999 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Inference for Cox s Regression Model Via a New Version of Empirical Likelihood written by Ali Jinnah and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Cox Proportional Hazard Model is one of the most popular tools used in the study of Survival Analysis. Empirical Likelihood (EL) method has been used to study the Cox Proportional Hazard Model. In recent work by Qin and Jing (2001), empirical likelihood based confidence region is constructed with the assumption that the baseline hazard function is known. However, in Cox's regression model the baseline hazard function is unspecified. In this thesis, we re-formulate empirical likelihood for the vector of regression parameters by estimating the baseline hazard function. The EL confidence regions are obtained accordingly. In addition, Adjusted Empirical Likelihood (AEL) method is proposed. Furthermore, we conduct extensive simulation studies to evaluate the performance of the proposed empirical likelihood methods in terms of coverage probabilities by comparing with the Normal Approximation based method. The simulation studies show that all the three methods produce similar coverage probabilities.
Download or read book Proportional Hazards Regression written by John O'Quigley and published by Springer Science & Business Media. This book was released on 2008-01-25 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The place in survival analysis now occupied by proportional hazards models and their generalizations is so large that it is no longer conceivable to offer a course on the subject without devoting at least half of the content to this topic alone. This book focuses on the theory and applications of a very broad class of models – proportional hazards and non-proportional hazards models, the former being viewed as a special case of the latter – which underlie modern survival analysis. Researchers and students alike will find that this text differs from most recent works in that it is mostly concerned with methodological issues rather than the analysis itself.
Download or read book Lifetime Data Models in Reliability and Survival Analysis written by Nicholas P. Jewell and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).
Download or read book R for Health Data Science written by Ewen Harrison and published by CRC Press. This book was released on 2020-12-31 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.
Download or read book Causal Inference with a Mediated Proportional Hazards Regression Model and a Mediated Accelerated Failure Time Model written by Hui Zeng and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The natural direct and indirect effects in causal mediation analysis with survival data having one mediator is addressed by VanderWeele (2011). He derived an approach for (1) an accelerated failure time regression model in general cases and (2) a proportional hazards regression model when the time-to-event outcome is rare. If the outcome is not rare, then VanderWeele (2011) did not derive a simple closed-form expression for the log-natural direct and log-natural indirect effects for the proportional hazards regression model because the baseline cumulative hazard function does not approach zero. We develop two approaches to extend VanderWeele's approach, in which the assumption of a rare outcome is not required. We obtain the natural direct and indirect effects for specific time points through numerical integration after we calculate the cumulative baseline hazard either by (1) applying the Breslow method in the Cox proportional hazards regression model to estimate the unspecified cumulative baseline hazard, or by (2) assuming a piecewise constant baseline hazard model, yielding a parametric model, to estimate the baseline hazard and cumulative baseline hazard. We also extend our two approaches to handle multiple mediators, which are in parallel and possibly correlated. For the accelerated failure time model, we extend the model to have multiple parallel mediators by defining variance-covariance matrix of mediators and develop the expression for the natural direct and indirect effects on the log mean survival time scale. We illustrate our approaches by applying them to data from the ASsessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Consortium.
Download or read book Goodness of Fit Tests and Model Validity written by C. Huber-Carol and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.
Download or read book Principles of Statistical Inference written by D. R. Cox and published by Cambridge University Press. This book was released on 2006-08-10 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
Download or read book Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data written by Mark Yuying An and published by . This book was released on 1998 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Inference in Mixed Proportional Hazard Models with K Random Effects written by Guillaume Horny and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general formulation of Mixed Proportional Hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. We then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the behavior of the estimator is assessed and I provide an application to the ratification of ILO conventions. Compared to other procedures, the results indicate an important decrease in computing time, as well as improved convergence and stability.
Download or read book Bootstrap based Inference for Cox s Proportional Hazards Analyses of Clustered Censored Survival Data written by Yongling Xiao and published by . This book was released on 2005 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Conclusions. The proposed bootstrap approach offers an easy-to-implement method to account for interdependence of times-to-events in the inference about Cox model regression parameters in the context of analyses of right-censored clustered data." --
Download or read book Proportional Hazards Transformation Models Partial Likelihood the Order Bootstrap and Adaptive Inference written by Kjell A. Doksum and published by . This book was released on 1983* with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Frailty Model written by Luc Duchateau and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Impact of Data dependent Model Selection on Inference written by Mamun Mahmud and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, I consider the problem of accounting for model uncertainty in a parametric regression model with focus on the uncertainty involved in selection of the optimal transformation of a continuous predictor in the Cox proportional hazards model (Cox, 1972). I use the minimum AIC approach to select a posteriori the optimal transformation of a continuous predictor. First, I review literature on criteria and methods for selecting the " best-fitting " model based on the results obtained from a sample, in Chapter 1. Then, in Chapter 2, I discuss the general problem of model selection uncertainty on inference and summarize research in this area. Next, I evaluate the impact of the data-dependent model selection approach on type I error rate through simulations. In simulations, I generate data, assuming both linear and non-linear dependence of hazard on a continuous covariate as well as no association. The generated data are then used to estimate a series of models with various functional form, to assess the impact of model selection on type I error and on statistical power. Some of the above methodological problems are then illustrated in the analysis of a real-life dataset including several cardiovascular risk factors.
