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The hybrid control design has the potential to improve efficiency but also carries the risk of introducing bias. The potential bias in a hybrid control study can be mitigated by adjusting for baseline covariates that are related to the control outcome. Existing methods that serve this purpose commonly assume that the internal and external control outcomes are exchangeable upon conditioning on a set of measured covariates. Possible violations of the exchangeability assumption can be addressed using a g\u2010computation method with variable selection under a correctly specified outcome regression model. In this article, we point out that a particular version of this g\u2010computation method is protected against misspecification of the outcome regression model. This observation leads to a model\u2010robust g\u2010computation method that is remarkably simple and easy to implement, consistent and asymptotically normal under minimal assumptions, and able to improve efficiency by exploiting similarities between the internal and external control groups. The method is evaluated in a simulation study and illustrated using real data from HIV treatment trials.<\/jats:p>","DOI":"10.1002\/sim.70754","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T05:13:17Z","timestamp":1790572397000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Model\u2010Robust G\u2010Computation Method for Analyzing Hybrid Control Studies Without Assuming Exchangeability"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3187-9180","authenticated-orcid":false,"given":"Zhiwei","family":"Zhang","sequence":"first","affiliation":[{"name":"Biostatistics Innovation Group Gilead Sciences  Foster City California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peisong","family":"Han","sequence":"additional","affiliation":[{"name":"Biostatistics Innovation Group Gilead Sciences  Foster City California 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