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J. Stat.<\/jats:italic>2006;<jats:bold>33<\/jats:bold>(4):637\u2013649) suggested to fit a Clayton copula with nonparametric marginal distributions to estimate the association for bivariate interval\u2010censored failure data. We propose here to model the marginal distributions with an accelerated failure time model with a flexible error term as suggested by Kom\u00e1rek<jats:italic>et al.<\/jats:italic>(<jats:italic>J. Comput. Graph. Stat.<\/jats:italic>2005;<jats:bold>14<\/jats:bold>(3):726\u2013745) in combination with a one parameter copula. In addition, we allow the association parameter of the copula to depend on covariates.<\/jats:p><jats:p>The performance of our method is illustrated by an extensive simulation study and is applied to tooth emergence data of permanent teeth measured on 4468 children from a longitudinal dental study. 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