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Nonparametric Analysis of Bivariate Censored Data

Nonparametric Analysis of Bivariate Censored Data
Author: Edward Popovich
Publisher:
Total Pages: 94
Release: 2019-05-31
Genre: Medical
ISBN: 9780530006406

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Abstract: A class of statistics is proposed for the problem of testing for location difference using censored matched pair data. The class consists of linear combinations of two conditionally independent statistics where the conditioning is on the number, N, of pairs in which both members are uncensored and the number, N", of pairs in which exactly one member is uncensored. Since every member of the class is conditionally distribution-free under the null hypothesis, H: no location difference, the statistics in the proposed class can be utilized to provide an exact conditional test of H for all N. and N.. If n denotes the total number of pairs, then under suitable conditions the proposed test statistics are shown to have asymptotic normal distributions as n tends to infinity. As a result, large sample tests can be performed using any member of the proposed class. A method that can be used to choose one test statistic from the proposed class of test statistics is outlined. However, the resulting test statistic depends on the underlying distributional forms of the populations from which the bivariate data and censoring variables are sampled. Simulation results indicate that the powers of certain members in the class are as good as and, in some cases, better than the power of a test for H proposed by Woolson and Lachenbruch in their paper titled "Rank Tests for Censored Matched Paris" appearing on pages 597-606 of Biometrika in 1980. Also, unlike the test of Woolson and Lachenbruch, the critical values for small samples can be tabulated for the tests in the new class. Consequently, members of the new class of tests are recommended for testing the null hypothesis. Dissertation Discovery Company and University of Florida are dedicated to making scholarly works more discoverable and accessible throughout the world. This dissertation, "Nonparametric Analysis of Bivariate Censored Data" by Edward Anthony Popovich, was obtained from University of Florida and is being sold with permission from the author. A digital copy of this work may also be found in the university's institutional repository, IR@UF. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation.


Nonparametric Analysis of Bivariate Censored Data

Nonparametric Analysis of Bivariate Censored Data
Author: Edward Anthony Popovich
Publisher: Palala Press
Total Pages: 90
Release: 2015-09-09
Genre:
ISBN: 9781342090942

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This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.


Nonparametric Statistical Methods For Complete and Censored Data

Nonparametric Statistical Methods For Complete and Censored Data
Author: M.M. Desu
Publisher: CRC Press
Total Pages: 384
Release: 2003-09-29
Genre: Mathematics
ISBN: 1482285894

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Balancing the "cookbook" approach of some texts with the more mathematical approach of others, Nonparametric Statistical Methods for Complete and Censored Data introduces commonly used non-parametric methods for complete data and extends those methods to right censored data analysis. Whenever possible, the authors derive their methodology from the general theory of statistical inference and introduce the concepts intuitively for students with minimal backgrounds. Derivations and mathematical details are relegated to appendices at the end of each chapter, which allows students to easily proceed through each chapter without becoming bogged down in a lot of mathematics. In addition to the nonparametric methods for analyzing complete and censored data, the book covers optimal linear rank statistics, clinical equivalence, analysis of block designs, and precedence tests. To make the material more accessible and practical, the authors use SAS programs to illustrate the various methods included. Exercises in each chapter, SAS code, and a clear, accessible presentation make this an outstanding text for a one-semester senior or graduate-level course in nonparametric statistics for students in a variety of disciplines, from statistics and biostatistics to business, psychology, and the social scientists. Prerequisites: Students will need a solid background in calculus and a two-semester course in mathematical statistics.


Nonparametric Tests for Censored Data

Nonparametric Tests for Censored Data
Author: Vilijandas Bagdonavicius
Publisher: John Wiley & Sons
Total Pages: 184
Release: 2013-02-07
Genre: Mathematics
ISBN: 1118602137

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This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.


METHODS FOR THE ANALYSIS OF CORRELATED CENSORED DATA.

METHODS FOR THE ANALYSIS OF CORRELATED CENSORED DATA.
Author: JANE M. OLSON
Publisher:
Total Pages: 288
Release: 1991
Genre:
ISBN:

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for estimation of both covariate effects and association. The first treats one of the failure times as a covariate in predicting the other and uses log-linear techniques to obtain parameter estimates. The second models the joint distribution of the residuals from a multivariate regression model as bivariate normal and obtains parameter estimates using the EM algorithm. The third extends the nonparametric regression methods of Buckley and James to the bivariate case.


The Statistical Analysis of Interval-censored Failure Time Data

The Statistical Analysis of Interval-censored Failure Time Data
Author: Jianguo Sun
Publisher: Springer
Total Pages: 304
Release: 2007-05-26
Genre: Mathematics
ISBN: 0387371192

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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.


Survival Analysis with Interval-Censored Data

Survival Analysis with Interval-Censored Data
Author: Kris Bogaerts
Publisher: CRC Press
Total Pages: 644
Release: 2017-11-20
Genre: Mathematics
ISBN: 1351643053

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Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features: -Provides an overview of frequentist as well as Bayesian methods. -Include a focus on practical aspects and applications. -Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website. The authors: Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials. Arnošt Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal. Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA.


Emerging Topics in Modeling Interval-Censored Survival Data

Emerging Topics in Modeling Interval-Censored Survival Data
Author: Jianguo Sun
Publisher: Springer Nature
Total Pages: 322
Release: 2022-11-29
Genre: Mathematics
ISBN: 3031123662

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This book primarily aims to discuss emerging topics in statistical methods and to booster research, education, and training to advance statistical modeling on interval-censored survival data. Commonly collected from public health and biomedical research, among other sources, interval-censored survival data can easily be mistaken for typical right-censored survival data, which can result in erroneous statistical inference due to the complexity of this type of data. The book invites a group of internationally leading researchers to systematically discuss and explore the historical development of the associated methods and their computational implementations, as well as emerging topics related to interval-censored data. It covers a variety of topics, including univariate interval-censored data, multivariate interval-censored data, clustered interval-censored data, competing risk interval-censored data, data with interval-censored covariates, interval-censored data from electric medical records, and misclassified interval-censored data. Researchers, students, and practitioners can directly make use of the state-of-the-art methods covered in the book to tackle their problems in research, education, training and consultation.


Nondetects and Data Analysis

Nondetects and Data Analysis
Author: Dennis R. Helsel
Publisher: Wiley-Interscience
Total Pages: 276
Release: 2005
Genre: Mathematics
ISBN:

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STATISTICS IN PRACTICE Statistical methods for interpreting and analyzing censored environmental data Nondetects And Data Analysis: Statistics for Censored Environmental Data provides solutions for environmental scientists and professionals who need to interpret and analyze data that fall below the laboratory detection limit. Adapting survival analysis methods that have been successfully used in medical and industrial research, the author demonstrates, for the first time, their practical applications for studies of trace chemicals in air, water, soils, and biota. Readers quickly become proficient in these methods through the use of real-world examples that are solved using MINITAB® Release 14, a popular statistical software package, as well as other commonly used software packages. Everything needed to master these innovative statistical methods is provided, including: Accompanying Web site featuring answers to book exercises and datasets, as well as MINITAB® macros to perform methods, which are not available in the commercial version Methods for data with multiple detection limits Solutions for research studies in which all data are below detection limits Techniques for constructing confidence, prediction, and tolerance intervals for data with nond-tects Methods for data with multiple detection limits Chapters are organized by objective, such as computing intervals, comparing groups, and correlations, which enables readers to more easily apply the text to their particular research and goals. Extensive references to the literature for more in-depth research are provided; however, the text itself avoids complex math and calculus making it accessible to anyone in the environmental sciences. Environmental scientists and professionals will find the hands-on guidance and practical examples invaluable.


Unified Methods for Censored Longitudinal Data and Causality

Unified Methods for Censored Longitudinal Data and Causality
Author: Mark J. van der Laan
Publisher: Springer Science & Business Media
Total Pages: 412
Release: 2012-11-12
Genre: Mathematics
ISBN: 0387217002

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A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.