Models For Repeated Measurements (oxford Statistical Science Series)

1. Basic Concepts -- 2. Fundamentals Of Modelling. 2.1. Statistical Models. 2.2. Specificities Of The Normal Distribution. 2.3. The Location Model. 2.4. Univariate Probability Distributions. 2.5. Families Of Multivariate Distributions. 2.6. Compound Distributions. 2.7. Conditional Models. 2.8. The Dynamic Generalized Linear Model. 2.9. Generalized Estimating Equations. 2.10. Stochastic Processes. 2.11. Inference -- 3. Heterogeneous Populations. 3.1. The Multivariate Normal Distribution. 3.2. Variance Components. 3.3. Random Effects Models. 3.4. Random Coefficients Models -- 4. Longitudinal Studies. 4.1. Autoregression Models. 4.2. A General Model. 4.3. The Dynamic Linear Model. 4.4. Parametric Growth Curves. 4.5. Crossover Studies. 4.6. Spectral Analysis -- 5. Overdispersion. 5.1. The Multivariate Multinomial Distribution. 5.2. Overdispersion In Count Data. 5.3. Nested Models. 5.4. Item Analysis -- 6. Longitudinal Discrete Data. 6.1. Markov Chains. 6.2. Autoregression. 6.3. Birth, Death, And Learning Models. 6.4. Crossover Trials. 6.5. Point Processes. 6.6. Generalized Estimating Equations -- 7. Frailty. 7.1. Characteristics Of Duration Data. 7.2. Models Without Dependence. 7.3. Compound Models -- 8. Event Histories. 8.1. Repeated Durations. 8.2. Distribution-based Models. 8.3. Intensity-based Models. 8.4. Stochastic Processes With Frailty. 8.5. Generalized Estimating Equations -- App. A Data Tables. A.1. Ultrafiltration Data. A.2. Coronary Sinus Potassium Data. A.3. Azams Data -- Afcr. A.4. Azams Data -- Doses. A.5. Blood Sugar Level Data. A.6. Epileptic Fit Data. A.7. Tumour Recurrence Data. A.8. Chronic Granulotomous Disease Data. A.9. Chronic Myeloid Leukemia Data. A.10. Mammary Tumour Data -- App. B Programs Used. J.k. Lindsey. Includes Bibliographical References (p. [303]-406) And Index.