6 citations · 10 across the 5 of their papers we have counts for
5 papers
Performance of Cross-Validated Targeted Maximum Likelihood Estimation
Matthew J. Smith, Rachael V. Phillips, Camille Maringe +1
Background: Advanced methods for causal inference, such as targeted maximum likelihood estimation (TMLE), require certain conditions for statistical inference. However, in situatio…
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…
On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables
Francisco J. Rubio, Bernard Rachet, Roch Giorgi +2
In cancer epidemiology using population-based data, regression models for the excess mortality hazard is a useful method to estimate cancer survival and to describe the association…