{ "_id": "6a27c67424555f66ed53f8b1", "Package": "TxEffectsSurvival", "Type": "Package", "Title": "Treatment Effect Inference for Terminal and Non-Terminal Events\nunder Competing Risks", "Version": "1.0.2", "Authors@R": "c(\nperson(given = \"Daewoo\", family = \"Pak\", email = \"dpak@yonsei.ac.kr\", role = c(\"aut\", \"cre\")),\nperson(given = \"Song\", family = \"Yang\", email = \"yangso@nhlbi.nih.gov\", role = c(\"aut\"))\n)", "Author": "Daewoo Pak [aut, cre], Song Yang [aut]", "Maintainer": "Daewoo Pak ", "Description": "Provides several confidence interval and testing\nprocedures, based on either semiparametric (using\nevent-specific win ratios) or nonparametric measures, including\nthe ratio of integrated cumulative hazard (RICH) and the ratio\nof integrated transformed cumulative hazard (RITCH), for\ntreatment effect inference with terminal and non-terminal\nevents under competing risks. The semiparametric results were\ndeveloped in Yang et al. (2022 ), and the\nnonparametric results were developed in Yang (2025\n). For comparison, results for the win\nratio (Finkelstein and Schoenfeld 1999\n),\nPocock et al. 2012 , and Bebu and\nLachin 2016 ) are included.\nThe package also supports univariate survival analysis with a\nsingle event. In this package, effect size estimates and\nconfidence intervals are obtained for each event type, and\nseveral testing procedures are implemented for the global null\nhypothesis of no treatment effect on either terminal or\nnon-terminal events. Furthermore, a test of proportional\nhazards assumptions, under which the event-specific win ratios\nconverge to hazard ratios, and a test of equal hazard ratios,\nare provided. For summarizing the treatment effect across all\nevents, confidence intervals for linear combinations of the\nevent-specific win ratios, RICH, or RITCH are available using\npre-determined or data-driven weights. Asymptotic properties of\nthese inference procedures are discussed in Yang et al. 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