Matthieu Resche-Rigon

发表

Multiple Imputation for Multilevel Data with Continuous and Binary Variables

Vincent Audigier, Stef van Buuren, Ian R. White, 2017, 1702.00971.

Multiple imputation for handling systematically missing confounders in meta‐analysis of individual participant data

Matthieu Resche-Rigon, Ian R White, Simon G Thompson, 2013, Statistics in medicine.

Assessing assay agreement estimation for multiple left‐censored data: a multiple imputation approach

Sylvie Chevret, Matthieu Resche-Rigon, Nathanael Lapidus, 2014, Statistics in medicine.

A multiple imputation approach for MNAR mechanisms compatible with Heckman's model

Sylvie Chevret, Matthieu Resche-Rigon, Jacques-Emmanuel Galimard, 2016, Statistics in medicine.

Combining multiple imputation and meta-analysis with individual participant data

Stephen Burgess, Matthieu Resche-Rigon, Ian R White, 2013, Statistics in medicine.

Heckman imputation models for binary or continuous MNAR outcomes and MAR predictors

Emmanuel Curis, Matthieu Resche-Rigon, Jacques-Emmanuel Galimard, 2018, BMC Medical Research Methodology.

THE LC-CUSUM: A QUANTITATIVE AND INDIVIDUALIZED ASSESSMENT OF THE LEARNING CURVE

Matthieu Resche-Rigon, Raphaël Porcher, David Biau, 2009 .

Clustering with missing and left‐censored data: A simulation study comparing multiple‐imputation‐based procedures

Matthieu Resche-Rigon, Emmanuel Curis, Vassili Soumelis, 2020, Biometrical journal. Biometrische Zeitschrift.

Clustering with missing data: which imputation model for which cluster analysis method?

Vincent Audigier, Matthieu Resche-Rigon, Ndeye Niang, 2021, 2106.04424.

The Physiological Deep Learner: First application of multitask deep learning to predict hypotension in critically ill patients

Yannet Interian, Matthieu Resche-Rigon, Romain Pirracchio, 2021, Artif. Intell. Medicine.

Comparison of two different generations of “NIRS” devices and transducers in healthy volunteers and ICU patients

Matthieu Resche-Rigon, Didier Payen, M. Resche-Rigon, 2013, Journal of Clinical Monitoring and Computing.

A “datathon” model to support cross-disciplinary collaboration

Leo Anthony Celi, Mengling Feng, Tristan Naumann, 2016, Science Translational Medicine.

Propensity score analysis with partially observed confounders: how should multiple imputation be used?

Clemence Leyrat, Liam Smeeth, Matthieu Resche-Rigon, 2016 .

Evaluation of the Propensity score methods for estimating marginal odds ratios in case of small sample size

Sylvie Chevret, Matthieu Resche-Rigon, Romain Pirracchio, 2012, BMC Medical Research Methodology.

Local influence for the subdistribution of a competing risk

Sylvie Chevret, Matthieu Resche-Rigon, S. Chevret, 2006, Statistics in medicine.

Analysing multicentre competing risks data with a mixed proportional hazards model for the subdistribution

Sylvie Chevret, Raphaël Porcher, Matthieu Resche-Rigon, 2006, Statistics in medicine.

Adaptive designs for dose-finding in non-cancer phase II trials: influence of early unexpected outcomes

Sarah Zohar, Sylvie Chevret, Matthieu Resche-Rigon, 2008, Clinical trials.

Using the continual reassessment method to estimate the minimum effective dose in phase II dose-finding studies: a case study

Sarah Zohar, Sylvie Chevret, Matthieu Resche-Rigon, 2013, Clinical trials.

Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm

Antoine Chambaz, Matthieu Resche-Rigon, Romain Pirracchio, 2020, Anesthesia and analgesia.

18F-FDG PET/CT for the Early Evaluation of Response to Neoadjuvant Treatment in Triple-Negative Breast Cancer: Influence of the Chemotherapy Regimen

Matthieu Resche-Rigon, Marc Espié, Pascal Merlet, 2016, The Journal of Nuclear Medicine.

Early non-invasive ventilation for acute respiratory failure in immunocompromised patients (IVNIctus): study protocol for a multicenter randomized controlled trial

Matthieu Resche-Rigon, Elie Azoulay, É. Azoulay, 2014, Trials.

Multiple imputation by chained equations for systematically and sporadically missing multilevel data

Matthieu Resche-Rigon, Ian R White, I. White, 2018, Statistical methods in medical research.

A new weighted balance measure helped to select the variables to be included in a propensity score model.

Sylvie Chevret, Matthieu Resche-Rigon, Romain Pirracchio, 2015, Journal of clinical epidemiology.

Propensity scores in intensive care and anaesthesiology literature: a systematic review

Raphaël Porcher, Matthieu Resche-Rigon, Romain Pirracchio, 2010, Intensive Care Medicine.

High Burden of Non-Influenza Viruses in Influenza-Like Illness in the Early Weeks of H1N1v Epidemic in France

François Simon, Matthieu Resche-Rigon, P. Taboulet, 2011, PloS one.