Nonlinear models for repeated measurement data
By Marie Davidian and David .M. Giltinan
"Nonlinear models for repeated measurement data" is published by Chapman & Hall/CRC in 1998 - Boca Raton, Fla, it has 359 pages and the language of the book is English.
“Nonlinear models for repeated measurement data” Metadata:
- Title: ➤ Nonlinear models for repeated measurement data
- Authors: Marie DavidianDavid .M. Giltinan
- Language: English
- Number of Pages: 359
- Publisher: Chapman & Hall/CRC
- Publish Date: 1998
- Publish Location: Boca Raton, Fla
“Nonlinear models for repeated measurement data” Subjects and Themes:
- Subjects: ➤ Biometry - Experimental design - Medical Statistics - Multivariate analysis - Nonlinear theories - Statistics - Nonlinear Dynamics - Statistical Models - Biométrie - Théories non linéaires - Biometrics - MATHEMATICS / Probability & Statistics / General - Biologie - Biomédecine - Méthodes statistiques - Méthodologie - Datenanalyse - Messung - Nichtlineares mathematisches Modell - Niet-lineaire modellen - Regressiemodellen - Análisis estadístico multivariable - Estadística matemática - Statistiques médicales - Regression analysis - Time-series analysis - Inference - Pharmacokinetics
Edition Specifications:
- Pagination: xv, 359 p. :
Edition Identifiers:
- The Open Library ID: OL3962153M - OL6220236W
- Online Computer Library Center (OCLC) ID: 33044478
- Library of Congress Control Number (LCCN): 2001265677
- ISBN-10: 0412983419
- All ISBNs: 0412983419
AI-generated Review of “Nonlinear models for repeated measurement data”:
"Nonlinear models for repeated measurement data" Description:
The Open Library:
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. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects model and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
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