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  "Title": "Weighted Estimation in Cox Regression",
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  "Authors@R": "c(\nperson(\"Daniela\", \"Dunkler\", email=\"daniela.dunkler@meduniwien.ac.at\", role=c(\"aut\", \"cre\")),\nperson(\"Georg\", \"Heinze\", role=\"aut\"),\nperson(\"Meinhard\", \"Ploner\", role=\"aut\"))",
  "Description": "Implements weighted estimation in Cox regression as\nproposed by Schemper, Wakounig and Heinze (Statistics in\nMedicine, 2009, <doi:10.1002/sim.3623>) and as described in\nDunkler, Ploner, Schemper and Heinze (Journal of Statistical\nSoftware, 2018, <doi:10.18637/jss.v084.i02>). Weighted Cox\nregression provides unbiased average hazard ratio estimates\nalso in case of non-proportional hazards. Approximated\ngeneralized concordance probability an effect size measure for\nclear-cut decisions can be obtained. The package provides\noptions to estimate time-dependent effects conveniently by\nincluding interactions of covariates with arbitrary functions\nof time, with or without making use of the weighting option.",
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