One-Step Targeted Minimum Loss-based Estimation Based on Universal Least Favorable One-Dimensional Submodels.

ABSTRACT: Consider a study in which one observes n independent and identically distributed random variables whose probability distribution is known to be an element of a particular statistical model, and one is concerned with estimation of a particular real valued pathwise differentiable target parameter of this data probability distribution. The targeted maximum likelihood estimator (TMLE) is an asymptotically efficient substitution estimator obtained by constructing a so called least favorable parametric submodel through an initial estimator with score, at zero fluctuation of the initial estimator, that spans the efficient influence curve, and iteratively maximizing the corresponding parametric likelihood till no more updates occur, at which point the updated initial estimator solves the so called

SUBMITTER: van der Laan M 

PROVIDER: S-EPMC4912007 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature