Date of Award
Doctor of Philosophy
Dr. Joshua Naranjo
Dr. Rajib Paul
Dr. Jung Chao Wang
Dr. Mark Schauer
Cox proportional hazards is the standard method for analyzing treatment efficacy when time-to-event data is available. In the absence of time-to-event, investigators may use logistic regression which only requires relative frequencies of events, or Poisson regression which requires only interval-summarized frequency tables of time-to-event. When event frequencies are used instead of time-to-events, does it always result in a loss in power?
We investigate the relative performance of the three methods. In particular, we compare the power of tests based on the respective effect-size estimates (1)hazard ratio (HR), (2)odds ratio (OR), and (3)risk ratio (RR). We use a variety of survival distributions and cut-off points representing length of study. We will show that the relative performance of OR against HR depends on the relative early-or-late separation of the two survival curves, and that OR and HR performed better than RR. We propose diagnostics based on the maximum separation to help investigators choose between OR and HR.
Dormitorio, Benedict P., "Comparison of Hazard, Odds and Risk Ratio in the Two-Sample Survival Problem" (2014). Dissertations. 304.