Ignoring the model selection step in inference after selection is harmful. This paper studies the asymptotic distribution of estimators after model selection using the Akaike information criterion. First, we consider the classical setting in which a true model exists and is included in the...

Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model averaging and post-model selection/averaging inference using likelihood methods in parametric models, along with associated confidence statements. In this paper, we consider a semiparametric version of...

Standard variable-selection procedures, primarily developed for the construction of outcome prediction models, are routinely applied when assessing exposure e®ects in observational studies. We argue that this tradition is sub-optimal and prone to yield bias in exposure effect estimates as well...