activity
20182025
most citedLogistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework

5 citations · 5 across the 4 of their papers we have counts for

collaborators
Showing stat.MEShow all

2 papers · 1 filter

stat.ME2024

Predictive Uncertainty Quantification with Missing Covariates

Margaux Zaffran, Julie Josse, Yaniv Romano +1

Predictive uncertainty quantification is crucial in decision-making problems. We investigate how to adequately quantify predictive uncertainty with missing covariates. A bottleneck…

stat.ME2018★ 5 cited

Logistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework

Wei Jiang, Julie Josse, Marc Lavielle +1

Logistic regression is a common classification method in supervised learning. Surprisingly, there are very few solutions for performing logistic regression with missing values in t…