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: 266
Release: 2017-10-24
Genre: Mathematics
ISBN: 135146664X

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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.

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.

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.

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.

Statistical Methods in Psychiatry and Related Fields

Statistical Methods in Psychiatry and Related Fields
Author: Ralitza Gueorguieva
Publisher: CRC Press
Total Pages: 371
Release: 2017-11-20
Genre: Mathematics
ISBN: 1498740774

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Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. Features Provides an overview of intermediate to advanced statistical methods applied to psychiatry. Takes a non-technical approach with mathematical details kept to a minimum. Includes lots of detailed examples from published studies in psychiatry and related fields. Software programs, data sets and output are available on a supplementary website. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.

Repeated Measurements and Cross-Over Designs

Repeated Measurements and Cross-Over Designs
Author: Damaraju Raghavarao
Publisher: John Wiley & Sons
Total Pages: 272
Release: 2014-04-14
Genre: Science
ISBN: 111870925X

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An introduction to state-of-the-art experimental design approaches to better understand and interpret repeated measurement data in cross-over designs. Repeated Measurements and Cross-Over Designs: Features the close tie between the design, analysis, and presentation of results Presents principles and rules that apply very generally to most areas of research, such as clinical trials, agricultural investigations, industrial procedures, quality control procedures, and epidemiological studies Includes many practical examples, such as PK/PD studies in the pharmaceutical industry, k-sample and one sample repeated measurement designs for psychological studies, and residual effects of different treatments in controlling conditions such as asthma, blood pressure, and diabetes. Utilizes SAS(R) software to draw necessary inferences. All SAS output and data sets are available via the book's related website. This book is ideal for a broad audience including statisticians in pre-clinical research, researchers in psychology, sociology, politics, marketing, and engineering.

Statistical Methods

Statistical Methods
Author: Rudolf J. Freund
Publisher: Elsevier
Total Pages: 694
Release: 2003-01-07
Genre: Mathematics
ISBN: 0080498221

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This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters