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After developing a general theory, we apply our methods to practically important situations where the candidate set of models, from which a working model is selected, consists of fixed design homoskedastic or heteroskedastic linear models, or of binary regression models with general link functions. In an extensive simulation study, we find that the proposed confidence intervals perform remarkably well, even when compared to existing methods that are tailored only for specific model selection procedures.<\/jats:p>","DOI":"10.1214\/19-aos1815","type":"journal-article","created":{"date-parts":[[2020,2,17]],"date-time":"2020-02-17T04:02:36Z","timestamp":1581912156000},"page":"440-463","source":"Crossref","is-referenced-by-count":35,"title":["Uniformly valid confidence intervals post-model-selection"],"prefix":"10.1214","volume":"48","author":[{"given":"Fran\u00e7ois","family":"Bachoc","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Preinerstorfer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lukas","family":"Steinberger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"108","reference":[{"key":"8","doi-asserted-by":"publisher","unstructured":"Efron, B., Hastie, T., Johnstone, I. and Tibshirani, R. 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