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This paper fills these important gaps by proposing distribution-free estimators for the Box\u2013Cox model with censoring in both the cross-sectional and panel data settings. The proposed methods are easy to implement by combining a convex minimization problem with a one-dimensional search. The procedures are applicable to other transformation models.<\/jats:p>","DOI":"10.1017\/s0266466611000703","type":"journal-article","created":{"date-parts":[[2011,11,25]],"date-time":"2011-11-25T10:44:28Z","timestamp":1322217868000},"page":"680-695","source":"Crossref","is-referenced-by-count":9,"title":["DISTRIBUTION-FREE ESTIMATION OF THE BOX\u2013COX REGRESSION MODEL WITH CENSORING"],"prefix":"10.1017","volume":"28","author":[{"given":"Songnian","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2011,11,25]]},"reference":[{"key":"S0266466611000703_ref35","unstructured":"Tian L. & Wei L.J. 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