Edited by Arni S.R. Srinivasa Rao, Saumyadipta Pyne, C.R. Rao
Volume 36,
Pages 2-493 (2017)
Chapter 1 - Fundamentals of Mathematical Models of Infectious Diseases and Their Application to Data Analyses
Chapter 2 - Dynamic Risk Prediction for Cardiovascular Disease: An Illustration Using the ARIC Study
Chapter 3 - Statistical Models for Selected Infectious Diseases
Chapter 4 - Finite Mixture Models in Biostatistics
Chapter 5 - Alternative Sampling Designs for Time-to-Event Data With Applications to Biomarker Discovery in Alzheimer's Disease
Chapter 6 - Real-Time Estimation of the Case Fatality Ratio and Risk Factors of Death
Chapter 7 - Nonparametric Regression of State Occupation Probabilities in a Multistate Model
Chapter 8 - Gene Set Analysis: As Applied to Public Health and Biomedical Studies
Chapter 9 - Causal Inference in the Study of Infectious Disease
Chapter 10 - Computational Modeling Approaches Linking Health and Social Sciences: Sensitivity of Social Determinants on the Patterns of Health Risk Behaviors and Diseases
Chapter 11 - Data-Driven Computational Disease Spread Modeling: From Measurement to Parametrization and Control
Chapter 12 - Individual and Collective Behavior in Public Health Epidemiology
Chapter 13 - Theoretical Advances in Type 2 Diabetes
Chapter 14 - Helminth Dynamics: Mean Number of Worms, Reproductive Rates
Chapter 15 - Bayesian Methods in Public Health
Chapter 16 - Bayesian Disease Mapping for Public Health