Zobrazeno 1 - 10
of 579
pro vyhledávání: '"Talbot Denis"'
Autor:
Diop, Awa, Sirois, Caroline, Guertin, Jason R., Schnitzer, Mireille E., Brophy, James M., Talbot, Denis
The R package trajmsm provides functions designed to simplify the estimation of the parameters of a model combining latent class growth analysis (LCGA), a trajectory analysis technique, and marginal structural models (MSMs) called LCGA-MSM. LCGA summ
Externí odkaz:
http://arxiv.org/abs/2410.19682
Autor:
Schnitzer, Mireille E, Talbot, Denis, Liu, Yan, Berger, David, Wang, Guanbo, O'Loughlin, Jennifer, Sylvestre, Marie-Pierre, Ertefaie, Ashkan
Causal variable selection in time-varying treatment settings is challenging due to evolving confounding effects. Existing methods mainly focus on time-fixed exposures and are not directly applicable to time-varying scenarios. We propose a novel two-s
Externí odkaz:
http://arxiv.org/abs/2410.08283
Autor:
Adenyo, David, Schnitzer, Mireille E, Berger, David, Guertin, Jason R, Candas, Bernard, Talbot, Denis
Criteria for identifying optimal adjustment sets (i.e., yielding a consistent estimator with minimal asymptotic variance) for estimating average treatment effects in parametric and nonparametric models have recently been established. In a single trea
Externí odkaz:
http://arxiv.org/abs/2410.01000
Marginal structural models have been increasingly used by analysts in recent years to account for confounding bias in studies with time-varying treatments. The parameters of these models are often estimated using inverse probability of treatment weig
Externí odkaz:
http://arxiv.org/abs/2403.08577
While the test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-19 vaccine surveillance, it is susceptible to selection bias due to outcome-dependent sampling
Externí odkaz:
http://arxiv.org/abs/2310.04578
Autor:
Talbot, Denis, Mésidor, Miceline, Trenou, Kossi Clément, Lavigne-Robichaud, Mathilde, Trudel, Xavier, Eslami, Aida
Population attributable fractions aim to quantify the proportion of the cases of an outcome (for example, a disease) that would have been avoided had no individuals in the population been exposed to a given exposure. This quantity thus plays a crucia
Externí odkaz:
http://arxiv.org/abs/2212.09538
The use of longitudinal finite mixture models such as group-based trajectory modeling has seen a sharp increase during the last decades in the medical literature. However, these methods have been criticized especially because of the data-driven model
Externí odkaz:
http://arxiv.org/abs/2205.07631
Publikováno v:
In Value in Health October 2024 27(10):1393-1399
The robust Poisson method is becoming increasingly popular when estimating the association of exposures with a binary outcome. Unlike the logistic regression model, the robust Poisson method yields results that can be interpreted as risk or prevalenc
Externí odkaz:
http://arxiv.org/abs/2112.00547
Precision medicine aims to tailor treatment decisions according to patients' characteristics. G-estimation and dynamic weighted ordinary least squares (dWOLS) are double robust statistical methods that can be used to identify optimal adaptive treatme
Externí odkaz:
http://arxiv.org/abs/2111.04844