{"ID":2838683,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.17379","arxiv_id":"2511.17379","title":"On treating right-censoring events like treatments","abstract":"In causal inference literature, potential outcomes are often indexed by the \"elimination of all right-censoring events,\" leading to the perception that such a restriction is necessary for defining well-posed causal estimands. In this paper, we clarify that this restriction is not required: a well-defined estimand can be formulated without indexing on the elimination of such events. Achieving this requires a more precise classification of right-censoring events than has historically been considered, as the nature of these events has direct implications for identification of the target estimand. We provide a framework that distinguishes different types of right-censoring events from a causal perspective, and demonstrate how this framework relates to censoring definitions and assumptions in classical survival analysis literature. By bridging these perspectives, we provide a clearer understanding of how to handle right-censoring events and provide guidance for identifying causal estimands when right-censored events are present.","short_abstract":"In causal inference literature, potential outcomes are often indexed by the \"elimination of all right-censoring events,\" leading to the perception that such a restriction is necessary for defining well-posed causal estimands. In this paper, we clarify that this restriction is not required: a well-defined estimand can b...","url_abs":"https://arxiv.org/abs/2511.17379","url_pdf":"https://arxiv.org/pdf/2511.17379v1","authors":"[\"Lan Wen\",\"Aaron L. Sarvet\",\"Jessica G. Young\"]","published":"2025-11-21T16:42:36Z","proceeding":"stat.ME","tasks":"[\"stat.ME\",\"math.ST\",\"stat.AP\"]","methods":"[]","has_code":false}