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Nonlinear models for repeated measurement data

Nonlinear models for repeated measurement data

Name: Nonlinear models for repeated measurement data

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Language: English

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Nonlinear mixed effects models for data in the form of continuous, repeated measurements on each of a number of individuals, also known as hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual-specific characteristics. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment. 15 Nov Nonlinear mixed effects models for data in the form of continuous, repeated measurements on each of a number of individuals, also known as hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual-specific characteristics.

roxfestny.com: Nonlinear Models for Repeated Measurement Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) (). Nonlinear Models for Repeated Measurement Data. Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. 15 Jul Marie Davidian and David M. Giltiman, Chapman and Hall, Great Britain, No. of pages: xv+ Price: £ ISBN: 0‐‐‐9.

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Nonlinear mixed effects models for data in the form of continuous, repeated. After reading the book for several weeks, there are positives and nega- tives. On the positive side, the text is short and to the point. It introduces simple linear. Nonlinear Models for Repeated Measurement Data. Neil H. Timm University of Pittsburgh. Pages | Published online: 12 Mar Pages Nonlinear Models for Repeated Measurement Data has 1 rating and 1 review. David said: What I learned from this book is that writing a book is a horrendou. Lindstrom, M. J. and Bates, D. M. (). Nonlinear mixed effects models for repeated measures data. Biometrics, 46, • Pinheiro, J. C., and Bates, D. M.

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