Analysis of Longitudinal Data and millions of other books are available for Amazon . of Longitudinal Data (Oxford Statistical Science Series) by Peter Diggle. : Analysis of Longitudinal Data (): Peter J. Diggle, Kung-Yee Liang, Scott L. Zeger: Books. Longitudinal Data Analysis. Peter Diggle Time series and longitudinal data: similarities/differences. 2. Linear models: Analysis of Bailrigg temperature data.

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Home Contact Us Help Free delivery worldwide. Analysis of Longitudinal Data. Description 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 analyysis 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 lonvitudinal 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 analydis 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 Dsta Books of Check out the top books of the year on our page Best Books of Looking for beautiful books?

Visit our Beautiful Books page and find lovely books for kids, photography lovers and more. Other books in this series. Analysis of Longitudinal Data Peter J. Saddlepoint Approximations Jens L. Procrustes Problems Garmt B.

Analysis of Longitudinal Data : Peter J. Diggle :

Statistical Modelling in R Murray Aitkin. Celebrating Statistics Nanny Wermuth. Smooth Tests of Goodness of Fit D. Table of contents 1.

Design considerations ; 3. Exploring longitudinal data ; 4. General linear models ; 5. Parametric models for covariance structure ; 6.

Analysis of longitudinal data – Peter Diggle, Kung-Yee Liang, Scott L. Zeger – Google Books

Analysis of variance methods ; 7. Generalized linear models for longitudinal data ; 8.

Marginal models ; 9. Random effects models ; Transition models ; Likelihood-based methods for categorical data ; Time-dependent covariates ; Missing values in longitudinal data ; Additional topics ; Appendix ; Bibliography ; Index show more. Review quote 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.


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.

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.

Analysis of Longitudinal Data

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