{ "_id": "6ac2036e773a0037682c0880", "Package": "EquiSurv", "Type": "Package", "Title": "Modeling, Confidence Intervals and Equivalence of Survival\nCurves", "Version": "0.1.0", "Author": "Kathrin Moellenhoff", "Maintainer": "Kathrin Moellenhoff ", "Description": "We provide a non-parametric and a parametric approach to\ninvestigate the equivalence (or non-inferiority) of two\nsurvival curves, obtained from two given datasets. The test is\nbased on the creation of confidence intervals at pre-specified\ntime points. For the non-parametric approach, the curves are\ngiven by Kaplan-Meier curves and the variance for calculating\nthe confidence intervals is obtained by Greenwood's formula.\nThe parametric approach is based on estimating the underlying\ndistribution, where the user can choose between a Weibull,\nExponential, Gaussian, Logistic, Log-normal or a Log-logistic\ndistribution. Estimates for the variance for calculating the\nconfidence bands are obtained by a (parametric) bootstrap\napproach. For this bootstrap censoring is assumed to be\nexponentially distributed and estimates are obtained from the\ndatasets under consideration. All details can be found in\nK.Moellenhoff and A.Tresch: Survival analysis under\nnon-proportional hazards: investigating non-inferiority or\nequivalence in time-to-event data .", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-04 07:25:31 UTC", "User": "root" }, "Repository": "https://kathrinmoellenhoff.r-universe.dev", "Date/Publication": "2020-09-23 12:30:02 UTC", "RemoteUrl": "https://github.com/cran/EquiSurv", "RemoteRef": "HEAD", "RemoteSha": "cf689a79afd6f0797464f148be8365bd2a4e3e08", "_user": "kathrinmoellenhoff", "_type": "src", "_file": "EquiSurv_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/3580eef0266501cc7693911601415f4f7615045fa877625c124b1d712b100c06", "_filesize": 146063, "_sha256": "3580eef0266501cc7693911601415f4f7615045fa877625c124b1d712b100c06", "_expires": "2027-01-12T07:42:36.000Z", "_created": "2026-10-04T07:25:31.000Z", "_published": "2026-10-04T07:42:38.374Z", "_jobs": [ { 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