- Number of credits: 2
- Course Duration: 24 Lectures
Preamble
Survival analysis is applied to data that specifies the time elapsed until an event. It is a mathematical tool of data analysis with wide applications for the study of censored data. Survival analysis can be applied to any branch of Economics to understand the event which includes the transition from failure to success. The objective of the course is to introduce students to survival analysis as a tool for data analysis both in theory and practice with the use of software packages like SPSS, SAS of STATA.
Pattern of Evaluation
The course is divided into two modules of 12 lectures each. The system of evaluation include theory and written assignment. The evaluation will be done through 40 marks of mid-semester exam and 60 marks of end-semester exam. The mid-semester exam includes written assignment of 20 marks
- 1. Fundamental Theorems of Probability,
Mathematical Expectation and Moments,
Probability Distribution; Discrete and
Continuous, Duration Models, Functions of
Survival Analysis, Survival Time,
Non-parametric Approach to Survival Analysis
Kaplan-Meier Estimate of Survival Function,
Product Limit Life Table, Estimate with
Censored Time.
- Life-History Analysis, Comparison of Survival Distributions, Parametric
Approach to Survival Analysis Cox Proportional Hazard Model-Basic form of
Hazard model, Interactions, Calculation of Life Table from the Proportional Hazard model, Inference and Goodness of Fit. Survival Models-Hazard models with Time Dependence, Time dependent Predictor Variables and Coefficients.
References
1.
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Hogg V Robert, Joseph W. Mckean and Allen T. Craig (2006). Introduction to Mathematical Statistics, Dorling Kindersely (India) Pvt. Ltd.New Delhi
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2.
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R.D. Retherford and Minja Choe (1993). Statistical Models for Causal
Analysis John Wiley and Sons Inc. New York.
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3. |
Lee E.T. (1992). Statistical Methods For Survival Data Analysis, John Wiley
& Sons Inc., New York.
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