58 citations · 105 across the 5 of their papers we have counts for
5 papers
Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review
Matthew J. Smith, Rachael V. Phillips, Miguel Angel Luque-Fernandez +1
The Targeted Maximum Likelihood Estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least…
The Delta-Method and Influence Function in Medical Statistics: a Reproducible Tutorial
Rodrigo Zepeda-Tello, Michael Schomaker, Camille Maringe +5
Approximate statistical inference via determination of the asymptotic distribution of a statistic is routinely used for inference in applied medical statistics (e.g. to estimate th…
Tutorial: Introduction to computational causal inference using reproducible Stata, R and Python code
Matthew J. Smith, Camille Maringe, Bernard Rachet +4
The purpose of many health studies is to estimate the effect of an exposure on an outcome. It is not always ethical to assign an exposure to individuals in randomised controlled tr…
Educational Note: Paradoxical Collider Effect in the Analysis of Non-Communicable Disease Epidemiological Data: a reproducible illustration and web application
Miguel Angel Luque-Fernandez, Michael Schomaker, Daniel Redondo-Sanchez +3
Classical epidemiology has focused on the control of confounding but it is only recently that epidemiologists have started to focus on the bias produced by colliders. A collider fo…
Using Longitudinal Targeted Maximum Likelihood Estimation in Complex Settings with Dynamic Interventions
Michael Schomaker, Miguel Angel Luque-Fernandez, Valeriane Leroy +1
Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dynamic treatment effects in the context of time-dependent confounding affected by…