Models for Repeated Measurements

Models for Repeated Measurements
Author: James K. Lindsey
Publisher: Oxford University Press, USA
Total Pages: 440
Release: 1993
Genre: Literary Criticism
ISBN:

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Here is an essential introduction to the latest arsenal of methods available to students and practicing scientists who undertake longitudinal and other studies that collect repeated measurements for subsequent analysis. The book presents the general context of repeated measurements and introduces--through a large number of concrete examples, including data tables--the three basic types of response variables: continuous (normal), categorical and count, and duration variables. The ways in which such repeated observations are interdependent, through heterogeneity and time dependence, are discussed. The author also develops a useful framework for constructing suitable models and introduces concepts of multivariate distributions and stochastic processes necessary to appreciate the underpinnings and power of repeated measurements analyses. The book concludes with an extensive bibliography of the repeated measurement literature that will aid readers interested in finding source materials. Written by a distinguished statistician, this book is a much-needed and practical guide to the most current repeated measurements techniques available. It will be welcomed by students, applied statisticians, biostatisticians, biologists, medical researchers, econometricians, sociologists, and psychologists.

Nonlinear Models for Repeated Measurement Data

Nonlinear Models for Repeated Measurement Data
Author: Marie Davidian
Publisher: Routledge
Total Pages: 360
Release: 2017-11-01
Genre: Mathematics
ISBN: 1351428152

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Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

Linear and Nonlinear Models for the Analysis of Repeated Measurements

Linear and Nonlinear Models for the Analysis of Repeated Measurements
Author: Edward Vonesh
Publisher: CRC Press
Total Pages: 590
Release: 1996-11-01
Genre: Mathematics
ISBN: 9780824782481

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Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.

Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials

Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials
Author: Toshiro Tango
Publisher: CRC Press
Total Pages: 376
Release: 2017-09-14
Genre: Mathematics
ISBN: 1498747906

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Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application of generalized linear mixed models and its related models in the statistical design and analysis of repeated measures from randomized controlled trials. The author introduces a new repeated measures design called S:T design combined with mixed models as a practical and useful framework of parallel group RCT design because of easy handling of missing data and sample size reduction. The book emphasizes practical, rather than theoretical, aspects of statistical analyses and the interpretation of results. It includes chapters in which the author describes some old-fashioned analysis designs that have been in the literature and compares the results with those obtained from the corresponding mixed models. The book will be of interest to biostatisticians, researchers, and graduate students in the medical and health sciences who are involved in clinical trials. Author Website:Data sets and programs used in the book are available at http://www.medstat.jp/downloadrepeatedcrc.html

Statistical Methods for the Analysis of Repeated Measurements

Statistical Methods for the Analysis of Repeated Measurements
Author: Charles S. Davis
Publisher: Springer Science & Business Media
Total Pages: 416
Release: 2008-01-10
Genre: Mathematics
ISBN: 0387215735

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A comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. It is designed to be both a useful reference for practitioners and a textbook for a graduate-level course focused on methods for the analysis of repeated measurements. The important features of this book include a comprehensive coverage of classical and recent methods for continuous and categorical outcome variables; numerous homework problems at the end of each chapter; and the extensive use of real data sets in examples and homework problems.

Analysis of Repeated Measures

Analysis of Repeated Measures
Author: Martin J. Crowder
Publisher: Routledge
Total Pages: 190
Release: 2017-10-24
Genre: Mathematics
ISBN: 1351466631

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Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.

Modeling Intraindividual Variability With Repeated Measures Data

Modeling Intraindividual Variability With Repeated Measures Data
Author: Scott L. Hershberger
Publisher: Psychology Press
Total Pages: 253
Release: 2013-06-17
Genre: Psychology
ISBN: 1135673209

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This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable. It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques. Each chapter features: a minimum discussion of mathematical detail; an empirical example applying the technique; and a discussion of the software related to that technique. Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.

Regression Methods in Biostatistics

Regression Methods in Biostatistics
Author: Eric Vittinghoff
Publisher: Springer Science & Business Media
Total Pages: 526
Release: 2012
Genre: Education
ISBN: 1461413524

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This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.

Multilevel Analysis

Multilevel Analysis
Author: Tom A. B. Snijders
Publisher: SAGE
Total Pages: 282
Release: 1999
Genre: Mathematics
ISBN: 9780761958901

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Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.

Analysis of Repeated Measures Data

Analysis of Repeated Measures Data
Author: M. Ataharul Islam
Publisher: Springer
Total Pages: 257
Release: 2017-07-06
Genre: Business & Economics
ISBN: 9811037949

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This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.