• Abstract
• Acknowledgments/Dedication
• Chapter 1. Introduction
  1. Motivating Data
  2. Naive Method and Problems
  3. Overview of Proposed Approach
  4. Review of Some Relevant Researches
  5. Researches Important to Future Development
• Chapter 2. The EM Algorithm
  1. The General EM Algorithm
  2. Mixed Models with Complete Data
  3. The Monte Carlo EM Algorithm
• Chapter 3. EM Algorithm for Censored Data
  1. Data Specification
  2. Likelihood Functions
  3. EM Algorithm with Censored Data
  4. Asymptotic Dispersion Matrix of MLE
• Chapter 4. Mixed Model with Censored Data
  1. Data Specification
  2. Distributions in the Exponential Families
  3. Multivariate Normal Distribution
• Chapter 5. Special Models For Normal Data
  1. Univariate Models with Censored Data
  2. Mixed Models without Censored Data
  3. Pure Random Effect Models
• Chapter 6. Sampling in MCEM Algorithm
  1. Sampling Scheme
  2. Sampling from Conditional Densities k₁ and k₂
  3. Mixed Models with Normal Distribution
• Chapter 7. Data Simulation and Example
  1. Data Simulation
  2. The Motivation Data with Random Intercept
  3. The Motivation Data with Random Slope
• Chapter 8. Discussion and Future Research
  1. Calculation of Complex Integrals
  2. More Specific Models
  3. Non-parametric Approach
  4. Data Analysis and Data Incompleteness
• Bibliography
• Appendix: Select Matrix Algebra
  1. Special Matrices and Operators
  2. Matrix Differentiation

Click here to show Dissertation Defense Committee Information

Dissertation Defense Committee       [ hide ]		12/21/2000
Dr. Myunghee Paik	Biostatistics
Dr. Wei-Yann Tsai	Biostatistics
Dr. Daniel Rabinowitz	Statistics
Dr. Frederica Perera	Environmental Health Sciences
Dr. LaVerne Mooney	Environmental Health Sciences

Last update: 3/1/2001