activity
20062026
most citedSafe Feature Elimination in Sparse Supervised Learning

178 citations · 324 across the 24 of their papers we have counts for

collaborators
Showing stat.MEShow all

11 papers · 1 filter

stat.ME2026

On the estimation of inclusion probabilities for weighted analyses of nested case control studies

Tomeu López-Nieto-Veitch, Rossella De Sabbata, Ryung Kim +3

Nested case-control (NCC) studies are a widely adopted design in epidemiology to investigate exposure-disease relationships. This paper examines weighted analyses in NCC studies, f…

stat.ME2020

On the use of cross-validation for the calibration of the adaptive lasso

Ballout Nadim, Etievant Lola, Viallon Vivian

The adaptive lasso refers to a class of methods that use weighted versions of the -norm penalty, with weights derived from an initial estimate of the parameter vector to be es…

stat.ME2020

On some limitations of probabilistic models for dimension-reduction: Illustration in the case of probabilistic formulations of partial least squares

Lola Etievant, Vivian Viallon

Partial Least Squares (PLS) refer to a class of dimension-reduction techniques aiming at the identification of two sets of components with maximal covariance, to model the relation…

stat.ME2019

Sparse estimation for case-control studies with multiple subtypes of cases

Nadim Ballout, Cedric Garcia, Vivian Viallon

The analysis of case-control studies with several subtypes of cases is increasingly common, e.g. in cancer epidemiology. For matched designs, we show that a natural strategy is bas…

stat.ME2019

Which practical interventions does the do-operator refer to in causal inference? Illustration on the example of obesity and cancer

Lola Etievant, Vivian Viallon

For exposures like obesity, no precise and unambiguous definition exists for the hypothetical intervention . This has raised concerns about the relevance of causal…

stat.ME2018★ 2 cited

Causal inference under over-simplified longitudinal causal models

Lola Etievant, Vivian Viallon

Many causal models of interest in epidemiology involve longitudinal exposures, confounders and mediators. However, repeated measurements are not always available or used in practic…