• Szilard Nemes University of Gothenburg, Sweden
Keywords: effect size, research design, exponential distribution


Restricted Mean Survival Time (RMST) is well-established, but underutilized measure that can be interpreted as the average event-free survival time up to a pre-specified time point. In the last decade RMST received substantial attention and was advocated as an alternative for the Hazard Rate when the proportionality assumption is not met. Currently studies with time-to-evet outcomes routinely report survival curves and hazard rates. Research planning assumes extraction of comparative effect measures and variances that facilitates sample size calculations. Here we assessed the possibility of extracting clinically meaningful effect size estimates for RMST based research plans from studies that report survival curves and hazard rates. This assessment was based on simulations using Exponential and Weibull distributions. The simulations suggest that under certain conditions meaningful RMST effect size estimates can be extrapolated form published hazard rates. However, in cases when the proportionality assumption is in doubt (i.e. when RMST have most utility) extraction of meaningful estimates is not feasible.


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How to Cite
Nemes, S. (2019). HAZARD RATES AND RESTRICTED MEAN SURVIVAL TIME. Indonesian Journal of Statistics and Its Applications, 3(3), 310-319. https://doi.org/10.29244/ijsa.v3i3.520