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Particularly challenging is differential recall bias in the context of self-reported binary exposures, where the bias may be directional rather than random and its extent varies according to the outcomes experienced. This paper makes several contributions: (1) it establishes bounds for the average treatment effect even when a validation study is not available; (2) it proposes multiple estimation methods across various strategies predicated on different assumptions; and (3) it suggests a sensitivity analysis technique to assess the robustness of the causal conclusion, incorporating insights from prior research. The effectiveness of these methods is demonstrated through simulation studies that explore various model misspecification scenarios. These approaches are then applied to investigate the effect of childhood physical abuse on mental health in adulthood.<\/jats:p>","DOI":"10.1093\/biomtc\/ujae058","type":"journal-article","created":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T06:38:58Z","timestamp":1719383938000},"source":"Crossref","is-referenced-by-count":21,"title":["Differential recall bias in estimating treatment effects in observational studies"],"prefix":"10.1093","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6077-1198","authenticated-orcid":false,"given":"Suhwan","family":"Bong","sequence":"first","affiliation":[{"name":"Department of Statistics, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwonsang","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Statistics, Seoul National University , Seoul 08826 , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Dominici","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Harvard T.H. 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