{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T03:28:30Z","timestamp":1784863710676,"version":"3.55.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,2,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>I propose a new type of confidence interval for correct asymptotic inference after using data to select a model of interest without assuming any model is correctly specified. This hybrid confidence interval is constructed by combining techniques from the selective inference and post-selection inference literatures to yield a short confidence interval across a wide range of data realizations. I show that hybrid confidence intervals have correct asymptotic coverage, uniformly over a large class of probability distributions that do not bound scaled model parameters. I illustrate the use of these confidence intervals in the problem of inference after using the lasso objective function to select a regression model of interest and provide evidence of their desirable length and coverage properties in small samples via a set of Monte Carlo experiments that entail a variety of different data distributions as well as an empirical application to the predictors of diabetes disease progression.<\/jats:p>","DOI":"10.1093\/biomet\/asad023","type":"journal-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:42:39Z","timestamp":1679618559000},"page":"109-127","source":"Crossref","is-referenced-by-count":4,"title":["Hybrid confidence intervals for informative uniform asymptotic inference after model selection"],"prefix":"10.1093","volume":"111","author":[{"given":"A","family":"McCloskey","sequence":"first","affiliation":[{"name":"Department of Economics, University of Colorado at Boulder , Boulder, Colorado 80309, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"2024021219291430600_asad023-B1","author":"Andrews","year":"2019"},{"key":"2024021219291430600_asad023-B2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.jeconom.2020.07.036","article-title":"Inference after estimation of breaks","volume":"224","author":"Andrews","year":"2021","journal-title":"J. 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