{ "_id": "6a101473acfb0bcc41c83aaf", "Package": "tteICE", "Type": "Package", "Title": "Treatment Effect Estimation for Time-to-Event Data with\nIntercurrent Events", "Version": "1.1.4", "Author": "Yuhao Deng [aut], Yi Zhou [cre]", "Maintainer": "Yi Zhou ", "Authors@R": "c(person(given = \"Yuhao\",\nfamily = \"Deng\",\nrole = \"aut\",\nemail = \"dengyuhao@pku.edu.cn\"),\nperson(given = \"Yi\",\nfamily = \"Zhou\",\nrole = \"cre\",\nemail = \"yzhou@pku.edu.cn\"))", "Description": "Analysis of treatment effects in clinical trials with\ntime-to-event outcomes is complicated by intercurrent events.\nThis package implements methods for estimating and inferring\nthe cumulative incidence functions for time-to-event (TTE)\noutcomes with intercurrent events (ICE) under the five\nstrategies outlined in the ICH E9 (R1) addendum, see Deng\n(2025) . This package can be used for\nanalyzing data from both randomized controlled trials and\nobservational studies. In general, the data involve a primary\noutcome event and, potentially, an intercurrent event. Two data\nstructures are allowed: competing risks, where only the time to\nthe first event is recorded, and semicompeting risks, where the\ntimes to both the primary outcome event and intercurrent event\n(or censoring) are recorded. 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