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Analysis Of Longitudinal Data

Author: Peter Diggle
Publisher: OUP Oxford
ISBN: 0191664332
Size: 23.98 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
Publisher: Springer Science & Business Media
ISBN: 9780387955568
Size: 80.36 MB
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During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time-dependent process. Such estimation problems arise in survival analysis, causal inference and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.

Medizinische Statistik

Author: Hans J. Trampisch
Publisher: Springer-Verlag
ISBN: 364256996X
Size: 20.46 MB
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"Statistiken sind merkwürdige Dinge ...", dies wird so mancher Mediziner denken, wenn er sich mit der Biometrie befaßt. Sei es im Rahmen seiner Ausbildung oder im Zuge wissenschaftlicher oder klinischer Studien, Kenntnisse der Statistik und Mathematik sind unentbehrlich für die tägliche Arbeit des Mediziners. Ziel dieses Lehrbuches ist es, den Mediziner systematisch an biometrische Terminologie und Arbeitsmethoden heranzuführen, um ihn schließlich mit den Grundlagen der Wahrscheinlichkeitsrechung vertraut zu machen. Nach der Lektüre dieses Buches hält der Leser ein Werkzeug in den Händen, das ihm bei der Lösung medizinscher Fragestellungen hilft ebenso wie bei der Beschreibung von Ergebnissen wissenschaftlicher Studien und natürlich bei der Doktorarbeit!

Nonparametric Analysis Of Longitudinal Data In Factorial Experiments

Author: Edgar Brunner
Publisher: Wiley-Interscience
ISBN:
Size: 75.57 MB
Format: PDF
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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
Publisher: Oxford University Press on Demand
ISBN: 9780198507055
Size: 38.28 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.

Nichtparametrische Analyse Longitudinaler Daten

Author: Edgar Brunner
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486798944
Size: 39.28 MB
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Das Buch richtet sich sowohl an Statistiker und Biometriker in der Praxis als auch an die Anwender, die sich mit den Auswertungsverfahren ihrer Daten und der näheren Beschreibung dieser Methoden beschäftigen möchten. Die Verfahren und Modelle werden anhand zahlreicher Beispiele aus Medizin, Pharmakologie und Forstwissenschaft dargestellt. Aus dem Inhalt: Modelle. Effekte und Hypothesen. Schätzer für die relativen Effekte. Teststatistiken. Software. Versuchsanlagen für eine Gruppe. Versuchsanlagen für mehrere Gruppen. Abhängige Meßwiederholungen. Mehrfaktorielle Versuchsanlagen. Zahlreiche Meßzeitpunkte. Ausblick und offene Probleme. Orginaldaten. Ergebnisse der SAS-Makros.