Mixed models : theory and applications with R /
"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 nume...
| Κύριος συγγραφέας: | |
|---|---|
| Μορφή: | Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Hoboken :
Wiley,
2013.
|
| Έκδοση: | Second [edition]. |
| Σειρά: | Wiley series in probability and statistics ;
893. |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Preface
- Preface to the Second Edition
- R software and functions
- Data Sets
- Open Problems in Mixed Models
- 1. Introduction: Why Mixed Models?
- 2. MLE for the 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.
