A weighted Harrell–Davis distance test with applications to censored data |
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Authors: | Dongliang Wang Alan D Hutson |
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Institution: | 1. Department of Public Health and Preventive Medicine, State University of New York Upstate Medical University, Syracuse, NY, USA;2. Department of Biostatistics, University at Buffalo, Buffalo, NY, USA |
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Abstract: | Consider the standard treatment-control model with a time-to-event endpoint. We propose a novel interpretable test statistic from a quantile function point of view. The large sample consistency of our estimator is proven for fixed bandwidth values theoretically and validated empirically. A Monte Carlo simulation study also shows that given small sample sizes, utilization of a tuning parameter through the application of a smooth quantile function estimator shows an improvement in efficiency in terms of the MSE when compared to direct application of classic Kaplan–Meier survival function estimator. The procedure is finally illustrated via an application to epithelial ovarian cancer data. |
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Keywords: | Censored data Distance test Expected shortfall Log-rank test Quantile function |
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