Mathematical methods in survival analysis reliability and quality of life 1st Edition by Catherine Huber, Nikolaos Limnios, Mounir Mesbah, Mikhail Nikulin ISBN 1848210108 9781848210103
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ISBN 10: 1848210108
ISBN 13: 9781848210103
Author: Catherine Huber, Nikolaos Limnios, Mounir Mesbah, Mikhail Nikulin
Mathematical methods in survival analysis reliability and quality of life 1st Table of contents:
Chapter 1: Introduction
1.1 Overview of Survival Analysis
1.2 Reliability Theory and Applications
1.3 Quality of Life Metrics
1.4 Historical Development and Key Concepts
1.5 Scope and Objectives of the Book
Chapter 2: Probability and Statistical Foundations
2.1 Probability Theory Refresher
2.2 Random Variables and Distributions
2.3 Common Survival and Reliability Distributions (Exponential, Weibull, Gompertz)
2.4 Censoring and Truncation
2.5 Moments, Expectations, and Variance
Chapter 3: Survival Functions and Hazard Rates
3.1 Survival Function and Cumulative Distribution Function
3.2 Hazard Function and Cumulative Hazard
3.3 Relationships Between Survival and Hazard
3.4 Life Table Methods
3.5 Kaplan-Meier Estimator
Chapter 4: Parametric Models for Survival Analysis
4.1 Exponential Model
4.2 Weibull Model
4.3 Gompertz and Log-normal Models
4.4 Maximum Likelihood Estimation
4.5 Model Comparison and Selection
Chapter 5: Non-Parametric and Semi-Parametric Methods
5.1 Kaplan-Meier Estimator Revisited
5.2 Nelson-Aalen Estimator
5.3 Cox Proportional Hazards Model
5.4 Model Diagnostics and Validation
5.5 Time-Dependent Covariates
Chapter 6: Reliability Analysis
6.1 Basic Concepts of Reliability
6.2 System Reliability: Series and Parallel Systems
6.3 Mean Time to Failure (MTTF) and Mean Residual Life
6.4 Stress-Strength Models
6.5 Reliability Growth Models
Chapter 7: Quality of Life Assessment
7.1 Definition and Importance
7.2 Measurement Scales and Instruments
7.3 Statistical Methods in QoL Studies
7.4 Longitudinal QoL Analysis
7.5 Integrating QoL with Survival Data
Chapter 8: Advanced Topics in Survival Analysis
8.1 Frailty Models
8.2 Competing Risks
8.3 Recurrent Event Data
8.4 Multistate Models
8.5 Bayesian Approaches in Survival Analysis
Chapter 9: Practical Applications
9.1 Clinical Trials and Medical Research
9.2 Engineering and Reliability Testing
9.3 Public Health and Policy Analysis
9.4 Case Studies in Quality of Life Research
9.5 Software Tools for Survival Analysis
Chapter 10: Conclusion and Future Directions
10.1 Summary of Key Concepts
10.2 Emerging Trends in Survival and Reliability Studies
10.3 Challenges and Opportunities
10.4 Final Remarks
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Tags: Catherine Huber, Nikolaos Limnios, Mounir Mesbah, Mikhail Nikulin, Mathematical methods