ΠΜΣ Βιοστατιστική: Ανάλυση Επιβίωσης
Constantin T. Yiannoutsos, Γιώργος Μπακογιάννης
This course will cover topics in analysis of failure time data. We will begin with an introduction to the central functions of survival analysis: the hazard, survival, and cumulative hazard functions. We will then consider nonparametric estimation of survival curves using Kaplan-Meier and actuarial estimation methods, and comparison of survival distributions using the logrank and other tests. The course will then turn to regression models for survival outcomes, with a heavy emphasis on aspects of the Cox proportional hazards model. Alternative models such as the accelerated failure time model and use of parametric distributions (exponential, Weibull) will also be considered. Class material will include presentation of statistical methods for estimation and testing, along with current software (mostly Stata, some SAS) for implementing analyses of survival data. Applications with real data will be emphasized.
LessThis course will cover topics in analysis of failure time data. We will begin with an introduction to the central functions of survival analysis: the hazard, survival, and cumulative hazard functions. We will then consider nonparametric estimation of survival curves using Kaplan-Meier and actuarial estimation methods, and comparison of survival distributions using the logrank and other tests. The course will then turn to regression models for survival outcomes, with a heavy emphasis on aspects of the Cox proportional hazards model. Alternative models such as the accelerated failure time model and use of parametric distributions (exponential, Weibull) will also be considered. Class material will include presentation of statistical methods for estimation and testing, along with current software (mostly Stata, some SAS) for implementing analyses of survival data. Applications with real data will be emphasized.
This course will cover topics in analysis of failure time data. We will begin with an introduction to the central functions of survival analysis: the hazard, survival, and cumulative hazard functions. We will then consider nonparametric estimation of survival curves using Kaplan-Meier and actuarial estimation methods, and comparison of survival distributions using the logrank and other tests. The course will then turn to regression models for survival outcomes, with a heavy emphasis on aspects of the Cox proportional hazards model. Alternative models such as the accelerated failure time model and use of parametric distributions (exponential, Weibull) will also be considered. Class material will include presentation of statistical methods for estimation and testing, along with current software (mostly Stata, some SAS) for implementing analyses of survival data. Applications with real data will be emphasized.
