KTH Matematik |

Seminarierummet 3721, Institutionen för Matematik, KTH, Lindstedts väg 25, plan 7.
Karta!
Survival time is often described by Kaplan-Meier curves. These can estimate percentiles of survival time like median survival, the time by which half of the patients would die. Other percentiles can be estimated as well like, for example, the 90th percentile of survival, the time by which 90% of the patients would die. Percentiles of survival may also be used to compare survival in different groups of patients (e.g. patients on treatment versus patients on placebo). The seminar gives an introduction to censored quantile regression with focus on Laplace regression, a general method for estimating percentiles of survival (e.g. median survival, 90th percentile of survival) that extends the Kaplan-Meier method to multivariable analyses in which multiple risk factors can be evaluated jointly and potential confounding adjusted for. The talk is meant for general audience with minimal familiarity with regression methods. Practical examples and results from analyses of simulated data will describe advantages and limitations of Laplace regression over other traditional approaches such as Cox proportional-hazard regression. Some mathematical details are given for completeness but are not essential for understanding the rest of the presentation. |

Sidansvarig: Filip Lindskog Uppdaterad: 25/02-2009 |