Survival analysis in the presence of complex censoring: Fractional Polynomials in Analyzing Interval-Censored Time-to-Event Data
Presented at JSM American Statistical Association
Interval censored time-to-event data along with complete-time and right/left-censored time-to-event are generated in most oncology clinical trials especially from cancer scan within some specific time intervals. The extension of the well-known Cox regression is discussed in this talk with fractional polynomials as the approximation to the baseline hazard function. A likelihood approach is used to select the best fractional polynomial as well as estimating the model parameters with associated statistical inference for treatment effect. The application of this method is demonstrated by a simulation study and to a real breast cancer clinical trial data
JSM American Statistical Association
Chen, Ding-Geng, Lili Yu, Yuhlong Lio.
"Survival analysis in the presence of complex censoring: Fractional Polynomials in Analyzing Interval-Censored Time-to-Event Data."
Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Presentations.