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presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be ap
Joint Modeling of Longitudinal and Time-to-Event Data
Multistate Models for the Analysis of Life History Data
Modern Biostatistical Methods for Evidence-Based Global Health Research
Dynamic Prediction in Clinical Survival Analysis
Statistical Modeling for Biological Systems
Statistical Modeling in Biomedical Research
Advanced Statistical Analytics for Health Data Science with SAS and R
Advanced Survival Models
Models for Multi-State Survival Data
Frontiers of Biostatistical Methods and Applications in Clinical Oncology
Biostatistics Modeling and Public Health Applications
Applied Biostatistical Principles and Concepts
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