#statisticsinmedicine — Public Fediverse posts
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Many clinical studies evaluate the benefit of a treatment based on both survival and other continuous/ordinal clinical outcomes, such as quality of life scores. In these studies, when subjects die before the follow-up assessment, the clinical outcomes become undefined and are truncated by death. Treating outcomes as “missing” or “censored” due to death can be misleading for treatment effect evaluation.
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Interesting reading: Kernel Cox partially linear regression.
Building kernel Cox proportional hazards semi-parametric model and regularized garrotized kernel machine (RegGKM) method to account wide heterogeneity in cancer patients’ survival due to molecular profiles. #stats #StatisticsInMedicine #statsodon