Mixed models : theory and applications

Author(s)

    • Demidenko, Eugene

Bibliographic Information

Mixed models : theory and applications

Eugene Demidenko

(Wiley series in probability and mathematical statistics)

Wiley-Interscience, c2004

Available at  / 29 libraries

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Note

Includes bibliographical references (p. [665]-695) and index

Description and Table of Contents

Description

A rigorous, self--contained examination of mixed model theory and application Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in--depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses:* Modeling of complex clustered or longitudinal data* Modeling data with multiple sources of variation* Modeling biological variety and heterogeneity* Mixed model as a compromise between the frequentist and Bayesian approaches* Mixed model for the penalized log--likelihood* Healthy Akaike Information Criterion (HAIC)* How to cope with parameter multidimensionality* How to solve ill--posed problems including image reconstruction problems* Modeling of ensemble shapes and images* Statistics of image processing Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.

Table of Contents

Preface. 1. Introduction: Why Mixed Models? 2. MLE for LME Model. 3. Statistical Properties of the LME Model. 4. Growth Curve Model and Generalizations. 5. Meta--analysis Model. 6. Nonlinear Marginal Model. 7. Generalized Linear Mixed Models. 8. Nonlinear Mixed Effects Model. 9. Diagnostics and Influence Analysis. 10. Tumor Regrowth Curves. 11. Statistical Analysis of Shape. 12. Statistical Image Analysis. 13. Appendix: Useful Facts and Formulas. References. Index.

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Details

  • NCID
    BA68693671
  • ISBN
    • 9780471601616
  • LCCN
    2004045643
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Hoboken, N.J.
  • Pages/Volumes
    xviii, 704 p.
  • Size
    25 cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
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