Generalized, Linear, and Mixed Models

摘要: Preface. Preface to the First Edition. 1. Introduction. 1.1 Models. 1.2 Factors, Levels, Cells, Effects And Data. 1.3 Fixed 1.4 Random 1.5 Linear Mixed Models (Lmms). 1.6 Or Random? 1.7 Inference. 1.8 Computer Software. 1.9 Exercises. 2. One-Way Classifications. 2.1 Normality Effects. 2.2 Normality, MLE. 2.3 REM1. 2.4 More On Normality. 2.5 Binary Data: 2.6 2.7 Computing. 2.8 3. Single-Predictor Regression. 3.1 3.2 Normality: Simple 3.3 A Nonlinear Model. 3.4 Transforming Versus Linking. 3.5 Intercepts: Balanced 3.6 Unbalanced 3.7 Bernoulli - Logistic 3.8 With Intercepts. 3.9 4. (LMs). 4.1 General 4.2 Model For 4.3 Mle Under 4.4 Sufficient Statistics. 4.5 Many Apparent Estimators. 4.6 Estimable Functions. 4.7 Numerical Example. 4.8 Estimating Residual Variance. 4.9 Comments The 1- 2-Way 4.10 Testing Hypotheses. 4.11 T-Tests Confidence Intervals. 4.12 Unique Estimation Using Restrictions. 4.13 5. Generalized (GLMs). 5.1 5.2 Structure Of 5.3 5.4 By Maximum Likelihood. 5.5 Tests 5.6 Quasi-Likelihood. 5.7 6. (LMMs). 6.1 6.2 Attributing To VAR(y). 6.3 V Known. 6.4 Unknown. 6.5 Predicting 6.6 6.7 Anova Variance Components. 6.8 Likelihood (Ml) Estimation. 6.9 Restricted (REMl). 6.10 Notes Extensions. 6.11 Appendix Chapter 6.12 7. 7.1 7.2 7.3 Consequences Having 7.4 7.5 Other Methods 7.6 7.7 Illustration: Chestnut Leaf Blight. 7.8 8. for Longitudinal data. 8.1 8.2 8.3 Approach. 8.4 Intercept Slope 8.5 8.6 Parameters. 8.7 8.8 Non-Normal Responses. 8.9 Summary Results. 8.10 Appendix. 8.11 9. Marginal 9.1 9.2 Examples Regression 9.3 Equations. 9.4 Contrasting Conditional 9.5 10. Multivariate 10.1 10.2 Normal Outcomes. 10.3 Non-Normally Distributed 10.4 Correlated 10.5 Based Analysis. 10.6 Example: Osteoarthritis Initiative. 10.7 10.8 11. 11.1 11.2 Corn Photosynthesis. 11.3 Pharmacokinetic 11.4 Computations 11.5 12. Departures From Assumptions. 12.1 12.2 Misspecifications Response. 12.3 Distribution. 12.4 Diagnose Correct Misspecifications. 12.5 13. Prediction. 13.1 13.2 Best Prediction (BP). 13.3 (BLP). 13.4 (BLUP). 13.5 Required 13.6 Estimated 13.7 Henderson's 13.8 13.9 14. 14.1 14.2 Computing Ml Estimates LMMs. 14.3 GLMMs. 14.4 Penalized Quasi-Likelihood Laplace. 14.5 M: Some Matrix M.1 Vectors Matrices Ones. M.2 Kronecker (Or Direct) Products. M.3 Notation. M.4 Inverses. M.5 Differential Calculus. S: Statistical S.1 Moments. S.2 Distributions. S.3 Exponential Families. S.4 S.5 Ratio Tests. S.6 MLE References. Index.