values. We offer a non-parametric plug-in estimator, the targeted maximum likelihood estimator (TMLE) and the cross …-validated TMLE (CV-TMLE), to simultaneously estimate both the average and variance of the stratum-specific treatment effect function …. The CV-TMLE is preferable because it guarantees asymptotic efficiency under two conditions without needing entropy …

recent methodological advances in the field of targeted maximum likelihood estimation (TMLE) and describe an estimation …-generating distribution. With this key insight in mind, we describe the TMLE for possibly-dependent units as an iid data algorithm and we …

investigation. In this article, we construct a new targeted minimum loss-based estimator (TMLE) for the effect or association of an …) estimator, augmented-IPTW and the standard TMLE algorithm. The new estimator yielded consistent estimates if either the … conditional mean outcome or the propensity score was consistently estimated. As a substitution estimator, TMLE guaranteed the …

estimation (TMLE). Through causal analysis, we operationalize the set of scientific questions that we wish to address regarding … the dative alternation. Drawing on the philosophy of TMLE, we answer these questions by targeting some versatile machine …

property, and discuss a class of estimators that have this property. We introduce a targeted minimum loss-based estimator (TMLE …. We investigate the new estimator’s performance relative to other estimators, including another TMLE, a propensity score …

minimum loss–based estimator (CV-TMLE) counterpart. These estimators are proven consistent and efficient under certain … estimators of the treatment and outcome mechanisms. Because the CV-TMLE is a substitution estimator, it is more robust than the … the CV-TMLE and the CV-A-IPTW are explored in a simulation study.  …