Download or read book The Statistical Analysis of Multivariate Failure Time Data written by Ross L. Prentice and published by CRC Press. This book was released on 2019-05-14 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women’s Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice. Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.
Download or read book The Statistical Analysis of Failure Time Data written by John D. Kalbfleisch and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Analysis of Multivariate Failure Time Data Based on Marginal Models written by Christian Bressen Pipper and published by . This book was released on 2003 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Analysis of Multivariate Interval censored Failure Time Data written by Man-Hua Chen and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A voluminous literature on right-censored failure time data has been developed in the past 30 years. Due to advances in biomedical research, interval censoring has become increasingly common in medical follow-up studies. In these cases, each study subject is examined or observed periodically, thus the observed failure time falls into a certain interval. Additional problems arise in the analysis of multivariate interval-censored failure time data. These include the estimating the correlation among failure times. The first part of this dissertation considers regression analysis of multivariate interval-censored failure time data using the proportional odds model. One situation in which the proportional odds model is preferred is when the covariate effects diminish over time. In contrast, if the proportional hazards model is applied for the situation, one may have to deal with time-dependent covariates. We present an inference approach for fitting the model to multivariate interval-censored failure time data. Simulation studies are conducted and an AIDS clinical trial is analyzed by using this methodology. The second part of this dissertation is devoted to the additive hazards model for multivariate interval-censored failure time data. In many applications, the proportional hazards model may not be appropriate and the additive hazards model provides an important and useful alternative. The presented estimates of regression parameters are consistent and asymptotically normal and a robust estimate of their covariance matrix is given that takes into account the correlation of the survival variables. Simulation studies are conducted for practical situations. The third part of this dissertation discusses regression analysis of multivariate interval censored failure time data using the frailty model approach. Based on the most commonly used regression model, the proportional hazards model, the frailty model approach considers the random effect directly models the correlation between multivariate failure times. For the analysis, we will focus on current status or case I interval-censored data and the maximum likelihood approach is developed for inference. The simulation studies are conducted to asses and compare the finite-sample behaviors of the estimators and we apply the proposed method to an animal tumorigenicity experiment.
Download or read book The Statistical Analysis of Failure Time Data written by John D. Kalbfleisch and published by Wiley-Interscience. This book was released on 1980 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Failure time models; Inference in parametric models and related topics; The proportional hazards model; Likelihood construction and further results on the proportional hazards model; Inference based on ranks in the accelerated failure time model; Multivariate failure time data and competing risks; Miscellaneous topics.
Download or read book The Statistical Analysis of Multivariate Failure Time Data written by Ross L. Prentice and published by CRC Press. This book was released on 2019-05-14 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women’s Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice. Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.
Download or read book Statistical Analysis of Multivariate Interval censored Failure Time Data written by Lianming Wang and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Interval-censored failure time data commonly arise in clinical trials and medical studies. In such studies, the failure time of interest is often not exactly observed, but known to fall within some interval. For multivariate interval-censored data, each subject may experience multiple events, each of which is interval-censored. This thesis studies four research problems related to regression analysis and association study of multivariate interval-censored data. In particular, in Chapter 2, we propose a goodness-of-fit test for the marginal Cox model approach, which is the most commonly, used approach in multivariate regression analysis. Chapter 3 presents a two-stage estimation procedure for the association parameter for case 2 bivariate interval-censored data. In Chapter 4 we give a simple procedure to estimate the regression parameter for case 2 interval-censored data and Chapter 5 studies the efficient estimation of regression parameters and association parameter simultaneously for bivariate current status data. All the proposed methods are assessed by simulation studies and illustrated using real-life applications.
Download or read book Linear Regression Analysis for Multivariate Failure Time Observations written by Jin-Sying Lin and published by . This book was released on 1991 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analysis of Multivariate Survival Data written by Philip Hougaard and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. As the field is rather new, the concepts and the possible types of data are described in detail. Four different approaches to the analysis of such data are presented from an applied point of view.
Download or read book The Statistical Analysis of Interval censored Failure Time Data written by Jianguo Sun and published by Springer. This book was released on 2007-05-26 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.
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 An Introduction to Multivariate Statistical Analysis written by Theodore Wilbur Anderson and published by John Wiley & Sons. This book was released on 1958 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multivariate normal distribution; Estimation of the mean vector and the covariance matrix; The distributions and uses of sample correlation coefficients; The generalized T2 statistic; Classification of observations; The distribution of the sample covariance matrix and the sample generalized variance; Testing the general linear hypothesis; analysis of variance; Testing independence of sets of variates; Testing hypotheses of equality of covariance matrices and equality of mean vectors and covariance matrices; Principal components; Canonical correlation and canonical variables; The distribution of certain characteristic roots and vectors that do not depend on parameters; A review of some other work in multivariate analysis.
Download or read book Statistical Analysis of Panel Count Data written by Jianguo Sun and published by Springer Science & Business Media. This book was released on 2013-10-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points. By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies, warranty claims of automobiles or system break-downs in reliability studies. In fact, many other fields yield event history data too such as demographic studies, economic studies and social sciences. For the cases where the study subjects are observed continuously, the resulting data are usually referred to as recurrent event data. This book collects and unifies statistical models and methods that have been developed for analyzing panel count data. It provides the first comprehensive coverage of the topic. The main focus is on methodology, but for the benefit of the reader, the applications of the methods to real data are also discussed along with numerical calculations. There exists a great deal of literature on the analysis of recurrent event data. This book fills the void in the literature on the analysis of panel count data. This book provides an up-to-date reference for scientists who are conducting research on the analysis of panel count data. It will also be instructional for those who need to analyze panel count data to answer substantive research questions. In addition, it can be used as a text for a graduate course in statistics or biostatistics that assumes a basic knowledge of probability and statistics.
Download or read book The Analysis of Multivariate Failure Time Data with Application to Multiple Endpoints in Trials in HIV Infection written by Ann Sarah Walker and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Multivariate Statistical Analysis written by Theodore W. Anderson and published by . This book was released on 1984-09-28 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Introduction; 2. The multivariate normal distribution; 3. Estimation of the mean vector and the covariance matrix; 4. Distributions and uses of sample correlation coefficients; 5. The generalized T2-Statistic; 6. Classification of observations; 7. The distribution of the sample covariance matrix and the sample generalized variance; 8. Testing the general linear hypothesis; Multivariate analysis of variance; 9. Testing independence of sets of variates; 10. Testing hypothesis of equality of coariance matrices and equality of mean vectors and covariance matrices; 11. Principal components; 12. Canonical correlations and canonical variables; 13. The distributions of characteristic roots and vectors; 14. Factor analysis.
Download or read book Omic Association Studies with R and Bioconductor written by Juan R. González and published by CRC Press. This book was released on 2019-06-14 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies. Newcomers to the field are confronted with a wealth of data, resources and methods. This book presents current methods to perform informative analyses using real and illustrative data with established bioinformatics tools and guides the reader through the use of publicly available data. Includes clear, readable programming codes for readers to reproduce and adapt to their own data. Emphasises extracting biologically meaningful associations between traits of interest and genomic, transcriptomic and epigenomic data Uses up-to-date methods to exploit omic data Presents methods through specific examples and computing sessions Supplemented by a website, including code, datasets, and solutions
Download or read book Survival Analysis State of the Art written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival analysis is a highly active area of research with applications spanning the physical, engineering, biological, and social sciences. In addition to statisticians and biostatisticians, researchers in this area include epidemiologists, reliability engineers, demographers and economists. The economists survival analysis by the name of duration analysis and the analysis of transition data. We attempted to bring together leading researchers, with a common interest in developing methodology in survival analysis, at the NATO Advanced Research Workshop. The research works collected in this volume are based on the presentations at the Workshop. Analysis of survival experiments is complicated by issues of censoring, where only partial observation of an individual's life length is available and left truncation, where individuals enter the study group if their life lengths exceed a given threshold time. Application of the theory of counting processes to survival analysis, as developed by the Scandinavian School, has allowed for substantial advances in the procedures for analyzing such experiments. The increased use of computer intensive solutions to inference problems in survival analysis~ in both the classical and Bayesian settings, is also evident throughout the volume. Several areas of research have received special attention in the volume.
