Advanced Survival Analysis

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  • 10 May 2013
  • statistics.com
  • Organiser: statistics.com
  • Event Details

This course builds upon the statistical methods covered in the Survival Analysis course at statistics.com. Discussion will focus on the extension of the Cox proportional hazards model to (a) recurrent event survival analysis and (b) competing risks survival analysis. The course will cover parametric survival models and frailty models and will conclude with discussion on the relative merits of parametric vs. semi-parametric techniques for modeling time-to-event data.

Course Program:

SESSION 1: Recurrent Event Survival Analysis
•The counting process approach for analyzing time-to-event data
•Survival curves for recurrent events
•Robust variance estimation
•Extension of the Cox proportional hazards model to accommodate recurrent events


SESSION 2: Competing Risks Survival Analysis
•Options for modeling competing risks
•Discussion of the independence assumption
•Survival curves for competing risks
•Implementation of competing risks data in Cox proportional hazards models using the Lunn-McNeil approach


SESSION 3: Parametric Survival Analysis
•Common distributions for time-to-event data (exponential, Weibull, log-logistic)
•The accelerated failure time model
•Parametric models for right-, left-, and interval-censored data


SESSION 4: Frailty (random intercept) Survival Analysis
•Purpose and assumptions of frailty models
•Incorporating frailties in parametric and semi-parametric survival analyses
•Discussion of the merits of parametric vs. semi-parametric survival models

Please note this is a four week online course.

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