ANALYSIS OF LONGITUDINAL DATA PETER DIGGLE PDF

Analysis of Longitudinal Data. 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.

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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. The book is readable, well-written, and amply illustrated - Technometrics, August previous edition.

It belongs in the possession of every statistician who encouters longitudinal data. The topics covered are too numerous to dwell on here If your work involves longitudinal data and you wish to update, this book will serve you very well. As a quick look-up, it is very useful.

The authors conclude each chapter with a helpful summary or conclusion, often indicating further reading.

Helpfully, they also mention the topics that they have chosen not to present, together with other recommended books for you to follow up They have also chosen a good selection of examples, many of them medical, with which the various methods are clearly illustrated.

Readers with interests across a wide spectrum of application areas will find the ideas relevant and interesting The book is readable and well written It belongs to the possession of every statistician who encounters longitudinal data. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.

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Please contact our Customer Service Team if you have any questions. Ebook This title is available as an ebook. To purchase, visit your preferred ebook provider. Oxford Scholarship Online Available in Oxford Scholarship Online - view abstracts and keywords at book and chapter level. The book is readable, well-written, and amply illustrated - Technometrics, August previous edition It belongs in the possession of every statistician who encouters longitudinal data.

Also of Interest. Gotelli, Aaron M. Siebert, Darcy Clay Siebert. Foundations of Info-Metrics Amos Golan. Mathematics of Evolution and Phylogeny Olivier Gascuel.

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Analysis of Longitudinal Data

Analysis of Longitudinal Data. 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.

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As a global organisation, we, like many others, recognize the significant threat posed by the coronavirus. During this time, we have made some of our learning resources freely accessible. Our distribution centres are open and orders can be placed online. Do be advised that shipments may be delayed due to extra safety precautions implemented at our centres and delays with local shipping carriers. This item is printed to order.

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