analysis of longitudinal data oxford statistical science series

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Analysis Of Longitudinal Data

Author : Peter Diggle
ISBN : 9780191664335
Genre : Mathematics
File Size : 73. 21 MB
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The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This second edition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.

Unified Methods For Censored Longitudinal Data And Causality

Author : Mark J. van der Laan
ISBN : 9780387217000
Genre : Mathematics
File Size : 75. 73 MB
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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.

Encyclopedia Of Quantitative Risk Analysis And Assessment

Author : Edward L. Melnick
ISBN : IND:30000123951398
Genre : Mathematical statistics
File Size : 86. 22 MB
Format : PDF
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Amstat News

Author :
ISBN : UOM:39015059048812
Genre : Statistics
File Size : 27. 68 MB
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Nonparametric Analysis Of Longitudinal Data In Factorial Experiments

Author : Edgar Brunner
ISBN : UOM:39015053516053
Genre : Business & Economics
File Size : 36. 75 MB
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The authoritative reference on nonparametric methods for evaluating longitudinal data in factorial designs Broadening the range of techniques that can be used to evaluate longitudinal data, Nonparametric Analysis of Longitudinal Data in Factorial Experiments presents nonparametric methods of evaluation that supplement the generalized linear models approach. Emphasizing the practical application of these methods in statistical procedures, this book provides a unified approach for the analysis of factorial designs involving longitudinal data that is appropriate for metric data, count data, ordered categorical data, and dichotomous data. Topics covered include nonparametric models, effects and hypotheses in experimental design, estimators for relative effects, experiments for one and several groups of subjects, multifactorial experiments, dependent replications, and experiments with numerous time points. The basic mathematical principles for the methods introduced here are described in theory, consistent with the book's minimal math requirements. Simple approximations for small data sets are provided, as well as ample chapter exercises to test skills, an appendix that includes original data for the examples used throughout the book, and downloadable SAS-IML macros for implementing the more extensive calculations. All applications are designed to be useful in many fields. Generously supplemented with more than 110 graphs and tables, Nonparametric Analysis of Longitudinal Data in Factorial Experiments is an essential reference for statisticians and biometricians, researchers in clinical trials, psychological studies, and in the fields of forestry, agriculture, sociology, ecology, and biology, as well as graduate students in statistics and biostatistics.

Symbolic Computation For Statistical Inference

Author : David F. Andrews
ISBN : 0198507054
Genre : Computers
File Size : 22. 33 MB
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The development of statistical computing has had a huge impact on the subject, freeing statisticians from the need to perform tedious calculations and allowing researchers to perform progressively more complex operations. This book gives a coherent presentation of the theory underlying the computations, and provides a framework where computer algorithms are used to do much of the calculation inherent in statistics. Beginning with an outline of algorithms to cover much of an undergraduate course in probability and statistics, it then goes on to discuss various common distributions, likelihood, bootstrap and sampling.

Biometrics

Author :
ISBN : UCAL:B5031673
Genre :
File Size : 38. 75 MB
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Journal Of Statistical Planning And Inference

Author : Elsevier Science (Firm)
ISBN : 03783758
Genre : Mathematics
File Size : 64. 77 MB
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Encyclopedia Of Statistical Sciences

Author : Samuel Kotz
ISBN : 0471743879
Genre : Mathematics
File Size : 31. 62 MB
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Entries cover statistical theory, methods, and applications. Includes the latest topics and advances made in statistical science over the past decade--in areas such as computer-intensive statistical methodology, genetics, medicine, the environment, and other applications.

Models For Intensive Longitudinal Data

Author : Theodore A. Walls
ISBN : 0198038666
Genre : Medical
File Size : 42. 80 MB
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Rapid technological advances in devices used for data collection have led to the emergence of a new class of longitudinal data: intensive longitudinal data (ILD). Behavioral scientific studies now frequently utilize handheld computers, beepers, web interfaces, and other technological tools for collecting many more data points over time than previously possible. Other protocols, such as those used in fMRI and monitoring of public safety, also produce ILD, hence the statistical models in this volume are applicable to a range of data. The volume features state-of-the-art statistical modeling strategies developed by leading statisticians and methodologists working on ILD in conjunction with behavioral scientists. Chapters present applications from across the behavioral and health sciences, including coverage of substantive topics such as stress, smoking cessation, alcohol use, traffic patterns, educational performance and intimacy. Models for Intensive Longitudinal Data (MILD) is designed for those who want to learn about advanced statistical models for intensive longitudinal data and for those with an interest in selecting and applying a given model. The chapters highlight issues of general concern in modeling these kinds of data, such as a focus on regulatory systems, issues of curve registration, variable frequency and spacing of measurements, complex multivariate patterns of change, and multiple independent series. The extraordinary breadth of coverage makes this an indispensable reference for principal investigators designing new studies that will introduce ILD, applied statisticians working on related models, and methodologists, graduate students, and applied analysts working in a range of fields. A companion Web site at www.oup.com/us/MILD contains program examples and documentation.

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