Mixed models. Theory and applications. (English) Zbl 1055.62086

Wiley Series in Probability and Statistics. Hoboken, NJ: John Wiley & Sons (ISBN 0-471-60161-6/hbk; 978-0-471-72843-6/ebook). xviii, 704 p. (2004).
This monograph provides a rigorous in-depth mathematical coverage of mixed model statistical properties as well as applications such as the analysis of tumor regrowth, shape, and image. The author discusses (among others) the following problems:
(i) modeling of complex clustered or longitudinal data, (ii) modeling data with multiple sources of variation, (iii) modeling biological varieties of heterogeneity, (iv) mixed models as a compromise between the frequentist an Bayesian approaches, (v) mixed models for the penalized log-likelihood, and Akaike information criterion, (vi) how to cope with parameter multidimensionality, (vii) how to solve ill-posed problems including image reconstruction problems, (viii) modeling of ensemble shapes and images, and (ix) statistics of image processing. Special attention is paid to numerical algorithms and their implementations.
This monograph is intended for professionals and students in a broad range of fields such as cancer research, computer science, engineering, and industry.


62J12 Generalized linear models (logistic models)
62-02 Research exposition (monographs, survey articles) pertaining to statistics
62P10 Applications of statistics to biology and medical sciences; meta analysis
62H35 Image analysis in multivariate analysis


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