52 citations · 106 across the 12 of their papers we have counts for
14 papers
What if we had built a prediction model with a survival super learner instead of a Cox model 10 years ago?
Arthur Chatton, Émilie Pilote, Kevin Assob Feugo +3
Objective: This study sought to compare the drop in predictive performance over time according to the modeling approach (regression versus machine learning) used to build a kidney…
Is checking for sequential positivity violations getting you down? Try sPoRT!
Arthur Chatton, Michael Schomaker, Miguel-Angel Luque-Fernandez +2
Background: Sequential positivity is often a necessary assumption for drawing causal inferences, such as through marginal structural modeling. Unfortunately, verification of this a…
Personalised dynamic super learning: an application in predicting hemodiafiltration convection volumes
Arthur Chatton, Michèle Bally, Renée Lévesque +3
Obtaining continuously updated predictions is a major challenge for personalised medicine. Leveraging combinations of parametric regressions and machine learning approaches, the pe…
Structured Learning in Time-dependent Cox Models
Guanbo Wang, Yi Lian, Archer Y. Yang +5
Cox models with time-dependent coefficients and covariates are widely used in survival analysis. In high-dimensional settings, sparse regularization techniques are employed for var…
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…
Integrating complex selection rules into the latent overlapping group Lasso for constructing coherent prediction models
Guanbo Wang, Sylvie Perreault, Robert W. Platt +3
The construction of coherent prediction models holds great importance in medical research as such models enable health researchers to gain deeper insights into disease epidemiology…
A general framework for formulating structured variable selection
Guanbo Wang, Mireille E. Schnitzer, Tom Chen +2
In variable selection, a selection rule that prescribes the permissible sets of selected variables (called a "selection dictionary") is desirable due to the inherent structural con…
Data Integration through outcome adaptive LASSO and a collaborative propensity score approach
Asma Bahamyirou, Mireille E. Schnitzer
Administrative data, or non-probability sample data, are increasingly being used to obtain official statistics due to their many benefits over survey methods. In particular, they a…
Modeling Treatment Effect Modification in Multidrug-Resistant Tuberculosis in an Individual Patient Data Meta-Analysis
Yan Liu, Mireille Schnitzer, Guanbo Wang +6
Effect modification occurs while the effect of the treatment is not homogeneous across the different strata of patient characteristics. When the effect of treatment may vary from i…
Doubly Robust Adaptive LASSO for Effect Modifier Discovery
Asma Bahamyirou, Mireille E. Schnitzer, Edward H. Kennedy +2
Effect modification occurs when the effect of the treatment on an outcome differs according to the level of a third variable (the effect modifier, EM). A natural way to assess effe…
Identifiability and estimation under the test-negative design with population controls with the goal of identifying risk and preventive factors for SARS-CoV-2 infection
Mireille E. Schnitzer, Daphna Harel, Vikki Ho +2
Due to the rapidly evolving COVID-19 pandemic caused by the SARS-CoV-2 virus, quick public health investigations of the relationships between behaviours and infection risk are esse…
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…
A causal inference approach to network meta-analysis
Mireille E. Schnitzer, Russell J. Steele, Michèle Bally +1
While standard meta-analysis pools the results from randomized trials that compare two treatments, network meta-analysis aggregates the results of randomized trials comparing a wid…
Effect of breastfeeding on gastrointestinal infection in infants: A targeted maximum likelihood approach for clustered longitudinal data
Mireille E. Schnitzer, Mark J. van der Laan, Erica E. M. Moodie +1
The PROmotion of Breastfeeding Intervention Trial (PROBIT) cluster-randomized a program encouraging breastfeeding to new mothers in hospital centers. The original studies indicated…