27.1.2015

We invite you to the mathematical statistics seminar "Delayed entry in Cox proportional hazards model". The Seminar will take place on Wednesday, February 4, 2015, 10:00 in Institute of Measurement Science SAs. Mgr. Silvie Bělašková from Mathematical Institute of Faculty of applied informatics, Tomas Bata University in Zlin, Czech Republic will present a talk.

Delayed entry in Cox proportional hazards model

Silvie Bělašková and Eva Fišerová

One of the primary goals of analysis of time scale in medicine is the estimation of treatment effects based on observational studies. These studies are often based on incomplete observations and it requires special techniques for analysing. Base methods often used are survival analysis. Methods of survival analysis (e.g., Cox proportional hazards model) require that the event time be measured with respect to some origin time. The choice of origin time is substantively important because it implies that the risk of the event varies as a function of time since that origin. Ideally, the origin time is the same as the time at which observations begin, on the other hand, observations do not begin until some time after the origin time. These late entries are treated as left truncated data in the statistical literature. However, in actual situations, it may be possible that subjects with either extremely high, or extremely low risk enter the study after the time origin. There are three tests that are commonly used to test the hypothesis that a covariate has no effect. These are Wald test, the score test and the likelihood ratio test. The aim of our contribution is discussing accuracy of p-value of these tests in proportional hazards model. 

Keywords

Survival analysis, Cox proportional hazards model, time scale, missing data. 

References