Julie Josse

Generating author description...

All published works

Action	Title	Year	Authors
+ PDF Chat	Expert Study on Interpretable Machine Learning Models with Missing Data	2024	Lena Stempfle Arthur James Julie Josse Tobias Gauss Fredrik Johansson
+ PDF Chat	Federated Causal Inference: Multi-Centric ATE Estimation beyond Meta-Analysis	2024	Rémi Khellaf Aurélien Bellet Julie Josse
+	To be or not to be, when synthetic data meet clinical pharmacology: A focused study on pharmacogenetics	2024	Jean‐Baptiste Woillard Clément Benoist Alexandre Destère Marc Labriffe Giulia Marchello Julie Josse Pierre Marquet
+ PDF Chat	Quantifying Treatment Effects: Estimating Risk Ratios in Causal Inference	2024	Ahmed Boughdiri Julie Josse Erwan Scornet
+	On the consistency of supervised learning with missing values	2024	Julie Josse Jacob M. Chen Nicolas Prost Gaël Varoquaux Erwan Scornet
+	Re-weighting the randomized controlled trial for generalization: finite-sample error and variable selection	2024	Bénédicte Colnet Julie Josse Gaël Varoquaux Erwan Scornet
+ PDF Chat	What Is a Good Imputation Under MAR Missingness?	2024	Jeffrey Näf Julie Josse
+ PDF Chat	Causal Inference Methods for Combining Randomized Trials and Observational Studies: A Review	2024	Bénédicte Colnet Imke Mayer Guanhua Chen Awa Dieng Ruohong Li Gaël Varoquaux Jean-Philippe Vert Julie Josse Shu Yang
+ PDF Chat	Generalizing treatment effects with incomplete covariates: Identifying assumptions and multiple imputation algorithms	2023	Imke Mayer Julie Josse
+	Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data	2023	Pan Zhao Julie Josse Shu Yang
+	Risk ratio, odds ratio, risk difference... Which causal measure is easier to generalize?	2023	Bénédicte Colnet Julie Josse Gaël Varoquaux Erwan Scornet
+	Conformal Prediction with Missing Values	2023	Margaux Zaffran Aymeric Dieuleveut Julie Josse Yaniv Romano
+	Variable importance for causal forests: breaking down the heterogeneity of treatment effects	2023	Clément Bénard Julie Josse
+	MMD-based Variable Importance for Distributional Random Forest	2023	Clément Bénard Jeffrey Näf Julie Josse
+	AdaptiveConformal: An R Package for Adaptive Conformal Inference	2023	Herbert Susmann Antoine Chambaz Julie Josse
+ PDF Chat	Reweighting the RCT for generalization: finite sample error and variable selection	2022	Bénédicte Colnet Julie Josse Gaël Varoquaux Erwan Scornet
+ PDF Chat	R-miss-tastic: a unified platform for missing values methods and workflows	2022	Imke Mayer Aude Sportisse Julie Josse Nicholas Tierney Nathalie Villa‐Vialaneix
+ PDF Chat	Robust Lasso‐Zero for sparse corruption and model selection with missing covariates	2022	Pascaline Descloux Claire Boyer Julie Josse Aude Sportisse Sylvain Sardy
+ PDF Chat	Document sans titre	2022	Consortium Icubam Laurent Bonnasse‐Gahot Maxime Dénès Gabriel Dulac-Arnold Sertan Girgin François Husson Valentin Iovene Julie Josse Antoine Kimmoun François P. Landes
+	Benchmarking missing-values approaches for predictive models on health databases v2	2022	Alexandre Pérez Gaël Varoquaux Marine Le Morvan Julie Josse Jean‐Baptiste Poline
+ PDF Chat	Causal effect on a target population: A sensitivity analysis to handle missing covariates	2022	Bénédicte Colnet Julie Josse Gaël Varoquaux Erwan Scornet
+ PDF Chat	Benchmarking missing-values approaches for predictive models on health databases	2022	Alexandre Pérez Gaël Varoquaux Marine Le Morvan Julie Josse Jean‐Baptiste Poline
+	Benchmarking missing-values approaches for predictive models on health databases	2022	Alexandre Pérez Gaël Varoquaux Marine Le Morvan Julie Josse Jean‐Baptiste Poline
+	Reweighting the RCT for generalization: finite sample error and variable selection	2022	Bénédicte Colnet Julie Josse Gaël Varoquaux Erwan Scornet
+ PDF Chat	Adaptive Bayesian SLOPE: Model Selection With Incomplete Data	2021	Wei Jiang Małgorzata Bogdan Julie Josse Szymon Majewski Błażej Miasojedow Veronika Ročková
+	Generalizing a causal effect: sensitivity analysis and missing covariates	2021	Bénédicte Colnet Julie Josse Erwan Scornet Gaël Varoquaux
+	Linear Regression and Logistic Regression with Missing Covariates [R package misaem version 1.0.1]	2021	Wei Jiang Julie Josse
+	Nonparametric Imputation by Data Depth	2021	Pavlo Mozharovskyi Julie Josse François Husson
+	What's a good imputation to predict with missing values?	2021	Marine Le Morvan Julie Josse Erwan Scornet Gaël Varoquaux
+	Model-based Clustering with Missing Not At Random Data	2021	Aude Sportisse Matthieu Marbac Christophe Biernacki Claire Boyer Gilles Celeux Julie Josse Fabien Laporte
+	Causal effect on a target population: a sensitivity analysis to handle missing covariates	2021	Bénédicte Colnet Julie Josse Erwan Scornet Gaël Varoquaux
+	Generalizing treatment effects with incomplete covariates: identifying assumptions and multiple imputation algorithms	2021	Imke Mayer Julie Josse Traumabase Group
+ PDF Chat	NeuMiss networks: differentiable programming for supervised learning with missing values	2020	Marine Le Morvan Julie Josse Thomas Moreau Erwan Scornet Gaël Varoquaux
+ PDF Chat	Causal inference methods for combining randomized trials and observational studies: a review	2020	Bénédicte Colnet Imke Mayer Guanhua Chen Awa Dieng Ruohong Li Gaël Varoquaux Jean‐Philippe Vert Julie Josse Shu Yang
+ PDF Chat	Doubly robust treatment effect estimation with missing attributes	2020	Imke Mayer Erik Sverdrup Tobias Gauss Jean-Denis Moyer Stefan Wager Julie Josse
+ PDF Chat	Imputation and low-rank estimation with Missing Not At Random data	2020	Aude Sportisse Claire Boyer Julie Josse
+	ICU Bed Availability Monitoring and analysis in the Grand Est region of France during the COVID-19 epidemic	2020	Consortium Icubam Laurent Bonnasse‐Gahot Maxime Dénès Gabriel Dulac-Arnold Sertan Girgin François Husson Valentin Iovene Julie Josse Antoine Kimmoun François P. Landes
+ PDF Chat	Robust Lasso-Zero for sparse corruption and model selection with missing covariates	2020	Pascaline Descloux Claire Boyer Julie Josse Aude Sportisse Sylvain Sardy
+	MissDeepCausal: causal inference from incomplete data using deep latent variable models	2020	Imke Mayer Julie Josse Félix Raimundo Jean-Philippe Vert
+	Missing Data Imputation using Optimal Transport	2020	Boris Muzellec Julie Josse Claire Boyer Marco Cuturi
+	NeuMiss networks: differentiable programming for supervised learning with missing values	2020	Marine Le Morvan Julie Josse Thomas Moreau Erwan Scornet Gaël Varoquaux
+	VARCLUST: clustering variables using dimensionality reduction	2020	Stanislaw Wilczynski Małgorzata Bogdan Piotr Sobczyk Stanisaaw Wilczy Maagorzata Bogdan Piotr Graczyk Julie Josse Fabien Panloup Valérie Seegers Mateusz Staniak
+	MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models	2020	Imke Mayer Julie Josse Félix Raimundo Jean‐Philippe Vert
+ PDF Chat	Logistic regression with missing covariates—Parameter estimation, model selection and prediction within a joint-modeling framework	2019	Wei Jiang Julie Josse Marc Lavielle
+	Doubly robust treatment effect estimation with missing attributes	2019	Imke Mayer Erik Sverdrup Tobias Gauss Jean-Denis Moyer Stefan Wager Julie Josse
+	Estimation with informative missing data in the low-rank model with random effects	2019	Aude Sportisse Claire Boyer Julie Josse
+ PDF Chat	Main Effects and Interactions in Mixed and Incomplete Data Frames	2019	Geneviève Robin Olga Klopp Julie Josse Éric Moulines Robert Tibshirani
+	Low-rank model with covariates for count data with missing values	2019	Geneviève Robin Julie Josse Éric Moulines Sylvain Sardy
+ PDF Chat	Imputation of Mixed Data With Multilevel Singular Value Decomposition	2019	François Husson Julie Josse Balasubramanian Narasimhan Geneviève Robin
+ PDF Chat	Hypothesis Tests for Principal Component Analysis When Variables are Standardized	2019	Johannes Forkman Julie Josse Hans‐Peter Piepho
+	Biases in feature selection with missing data	2019	Borja Seijo-Pardo Amparo Alonso‐Betanzos Kristin P. Bennett Verónica Bolón‐Canedo Julie Josse Mehreen Saeed Isabelle Guyon
+ PDF Chat	Nonparametric Imputation by Data Depth	2019	Pavlo Mozharovskyi Julie Josse François Husson
+	Imputation and low-rank estimation with Missing Non At Random data	2019	Aude Sportisse Claire Boyer Julie Josse
+	Imputation of Mixed Data With Multilevel Singular Value Decomposition	2019	François Husson Julie Josse Balasubramanian Narasimhan Geneviève Robin
+	Main Effects and Interactions in Mixed and Incomplete Data Frames	2019	Geneviéve Robin Olga Klopp Julie Josse Éric Moulines Robert Tibshirani
+	On the consistency of supervised learning with missing values	2019	Julie Josse Nicolas Prost Erwan Scornet Gaël Varoquaux
+	Adaptive Bayesian SLOPE -- High-dimensional Model Selection with Missing Values	2019	Wei Jiang Małgorzata Bogdan Julie Josse Błażej Miasojedow Veronika Ročková
+	Estimation and imputation in Probabilistic Principal Component Analysis with Missing Not At Random data	2019	Aude Sportisse Claire Boyer Julie Josse
+	Nonparametric imputation by data depth	2019	Pavlo Mozharovskyi Julie Josse François Husson
+	Doubly robust treatment effect estimation with missing attributes	2019	Imke Mayer Erik Sverdrup Tobias Gauss Jean-Denis Moyer Stefan Wager Julie Josse
+	Nonparametric Imputation by Data Depth	2019	Pavlo Mozharovskyi Julie Josse François Husson
+	misaem: Linear Regression and Logistic Regression with Missing Covariates	2018	Wei Jiang Julie Josse
+	Stochastic Approximation EM for Logistic Regression with Missing Values	2018	Wei Jiang Julie Josse Marc Lavielle
+ PDF Chat	Introduction to the Special Section on Missing Data	2018	Julie Josse Jerome P. Reiter
+	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames	2018	Geneviève Robin Hoi-To Wai Julie Josse Olga Klopp Éric Moulines
+	Analysis of imputation bias for feature selection with missing data.	2018	Borja Seijo-Pardo Amparo Alonso‐Betanzos Kristin P. Bennett Verónica Bolón‐Canedo Isabelle Guyon Julie Josse Mehreen Saeed
+	Logistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework	2018	Wei Jiang Julie Josse Marc Lavielle
+	Main effects and interactions in mixed and incomplete data frames	2018	Geneviéve Robin Olga Klopp Julie Josse Éric Moulines Robert Tibshirani
+	Imputation of mixed data with multilevel singular value decomposition	2018	François Husson Julie Josse Balasubramanian Narasimhan Geneviéve Robin
+	Discussion of “50 Years of Data Science”	2017	Susan Holmes Julie Josse
+ PDF Chat	Low-rank Interaction Contingency Tables	2017	Geneviéve Robin Julie Josse Éric Moulines Sylvain Sardy
+ PDF Chat	Bayesian Dimensionality Reduction With PCA Using Penalized Semi-Integrated Likelihood	2017	Piotr Sobczyk Małgorzata Bogdan Julie Josse
+	Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig	2017	Christian P. Robert Gilles Celeux Jack Jewson Julie Josse Jean‐Michel Marin Christian P. Robert
+	Empirical Bayes approaches to PageRank type algorithms for rating scientific journals	2017	Jean‐Louis Foulley Gilles Celeux Julie Josse
+	Low-rank model with covariates for count data analysis	2017	Geneviève Robin Julie Josse Éric Moulines Sylvain Sardy
+	Nonparametric imputation by data depth	2017	Pavlo Mozharovskyi Julie Josse François Husson
+ PDF Chat	MIMCA: multiple imputation for categorical variables with multiple correspondence analysis	2016	Vincent Audigier François Husson Julie Josse
+	denoiseR: A Package for Low Rank Matrix Estimation	2016	Julie Josse Sylvain Sardy Stefan Wager
+	Multinomial Multiple Correspondence Analysis	2016	Patrick J. F. Groenen Julie Josse
+	<b>missMDA</b>: A Package for Handling Missing Values in Multivariate Data Analysis	2016	Julie Josse François Husson
+ PDF Chat	Measuring multivariate association and beyond	2016	Julie Josse Susan Holmes
+	Multiple Correspondence Analysis & the Multilogit Bilinear Model	2016	William Fithian Julie Josse
+	Bootstrap-based regularization for low-rank matrix estimation	2016	Julie Josse Stefan Wager
+	Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood	2016	Piotr Sobczyk Małgorzata Bogdan Julie Josse
+ PDF Chat	Multiple imputation for continuous variables using a Bayesian principal component analysis	2015	Vincent Audigier François Husson Julie Josse
+ PDF Chat	Confidence Areas for Fixed-Effects PCA	2015	Julie Josse Stefan Wager François Husson
+	MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis	2015	Vincent Audigier François Husson Julie Josse
+ PDF Chat	Adaptive shrinkage of singular values	2015	Julie Josse Sylvain Sardy
+	Stable Autoencoding: A Flexible Framework for Regularized Low-rank Matrix Estimation	2015	Julie Josse Stefan Wager
+	MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis	2015	Vincent Audigier François Husson Julie Josse
+	A principal component method to impute missing values for mixed data	2014	Vincent Audigier François Husson Julie Josse
+	Principal component analysis with missing values: a comparative survey of methods	2014	Stéphane Dray Julie Josse
+	Bootstrap-Based Regularization for Low-Rank Matrix Estimation	2014	Julie Josse Stefan Wager
+	Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation	2014	Julie Josse Stefan Wager
+	Confidence Areas for Fixed-Effects PCA	2014	Julie Josse Stefan Wager François Husson
+	Multiple imputation for continuous variables using a Bayesian principal component analysis	2014	Vincent Audigier François Husson Julie Josse
+	Multiple imputation for continuous variables using a Bayesian principal component analysis	2014	Vincent Audigier François Husson Julie Josse
+	Confidence Areas for Fixed-Effects PCA	2014	Julie Josse Stefan Wager François Husson
+ PDF Chat	Regularised PCA to denoise and visualise data	2013	Marie Verbanck Julie Josse François Husson
+	Selecting thresholding and shrinking parameters with generalized SURE for low rank matrix estimation	2013	Julie Josse Sylvain Sardy
+	Adaptive Shrinkage of singular values	2013	Julie Josse Sylvain Sardy
+	Measures of dependence between random vectors and tests of independence. Literature review	2013	Julie Josse Susan Holmes
+	A principal components method to impute missing values for mixed data	2013	Vincent Audigier François Husson Julie Josse
+	Regularised PCA to denoise and visualise data	2013	Marie Verbanck Julie Josse François Husson
+	Measures of dependence between random vectors and tests of independence. Literature review	2013	Julie Josse Susan Holmes
+	A principal components method to impute missing values for mixed data	2013	Vincent Audigier François Husson Julie Josse
+	Regularised PCA to denoise and visualise data	2013	Marie Verbanck Julie Josse François Husson
+	Adaptive Shrinkage of singular values	2013	Julie Josse Sylvain Sardy
+	Handling missing values in exploratory multivariate data analysis methods	2012	Julie Josse François Husson
+	Selecting the number of components in principal component analysis using cross-validation approximations	2011	Julie Josse François Husson
+	Multiple imputation in principal component analysis	2011	Julie Josse Jérôme Pagès François Husson
+	Analyse de données avec R - Complémentarité des méthodes d'analyse factorielle et de classification	2010	François Husson Julie Josse Jérôme Pagès
+	Principal component methods - hierarchical clustering - partitional clustering: why would we need to choose for visualizing data?	2010	Julie Josse
+	Variabilité des dimensions en ACP : cas complet et incomplet	2010	Julie Josse François Husson
+	<b>FactoMineR</b>: An<i>R</i>Package for Multivariate Analysis	2008	Sébastien Lê Julie Josse François Husson

Common Coauthors

Coauthor	Papers Together
François Husson	32
Gaël Varoquaux	17
Erwan Scornet	14
Stefan Wager	11
Imke Mayer	10
Geneviéve Robin	10
Sylvain Sardy	10
Vincent Audigier	9
Claire Boyer	8
Wei Jiang	7
Éric Moulines	7
Aude Sportisse	7
Marine Le Morvan	6
Pavlo Mozharovskyi	5
Małgorzata Bogdan	5
Olga Klopp	4
Tobias Gauss	4
Susan Holmes	4
Bénédicte Colnet	3
Alexandre Pérez	3
Jean‐Baptiste Poline	3
Jean-Denis Moyer	3
Erik Sverdrup	3
Bénédicte Colnet	3
Gilles Celeux	3
Piotr Sobczyk	3
Bénédicte Colnet	3
Marc Lavielle	3
Robert Tibshirani	3
Marie Verbanck	3
Shu Yang	3
Borja Seijo-Pardo	2
Balasubramanian Narasimhan	2
Clément Bénard	2
Thomas Moreau	2
Pierre Guillaume Raverdy	2
Laurent Bonnasse-Gahot	2
Verónica Bolón‐Canedo	2
Nicolas Prost	2
Pascaline Descloux	2
Félix Raimundo	2
Gabriel Dulac-Arnold	2
Vincent Rouvreau	2
Roman Yurchak	2
Valentin Iovene	2
Antoine Kimmoun	2
Olivier Teboul	2
Jean‐Philippe Vert	2
Błażej Miasojedow	2
Isabelle Guyon	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	28
+	Inference and missing data	1976	Donald B. Rubin	23
+	Statistical Analysis With Missing Data	1989	Maureen Lahiff Roderick J. A. Little Donald B. Rubin	21
+	Multiple Imputation for Nonresponse in Surveys	1987	Donald B. Rubin	19
+	<b>mice</b>: Multivariate Imputation by Chained Equations in<i>R</i>	2011	Stef van Buuren Catharina G. M. Groothuis‐Oudshoorn	18
+	<b>missMDA</b>: A Package for Handling Missing Values in Multivariate Data Analysis	2016	Julie Josse François Husson	15
+	<b>FactoMineR</b>: An<i>R</i>Package for Multivariate Analysis	2008	Sébastien Lê Julie Josse François Husson	15
+	Flexible Imputation of Missing Data	2012	Stef van Buuren	14
+ PDF Chat	MissForest—non-parametric missing value imputation for mixed-type data	2011	Daniel J. Stekhoven Peter Bühlmann	14
+	Spectral Regularization Algorithms for Learning Large Incomplete Matrices.	2010	Rahul Mazumder Trevor Hastie Robert Tibshirani	12
+	Selecting the number of components in principal component analysis using cross-validation approximations	2011	Julie Josse François Husson	11
+	Principal Component Analysis	2005	Ian T. Jolliffe	11
+	Reconstruction of a low-rank matrix in the presence of Gaussian noise	2013	Andrey A. Shabalin Andrew B. Nobel	11
+	Handling missing values in exploratory multivariate data analysis methods	2012	Julie Josse François Husson	10
+ PDF Chat	Logistic regression with missing covariates—Parameter estimation, model selection and prediction within a joint-modeling framework	2019	Wei Jiang Julie Josse Marc Lavielle	10
+ PDF Chat	Regularised PCA to denoise and visualise data	2013	Marie Verbanck Julie Josse François Husson	10
+ PDF Chat	The Power of Convex Relaxation: Near-Optimal Matrix Completion	2010	Emmanuel J. Candès Terence Tao	9
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	9
+	Weighted least squares fitting using ordinary least squares algorithms	1997	Henk A. L. Kiers	9
+ PDF Chat	Unbiased Risk Estimates for Singular Value Thresholding and Spectral Estimators	2013	Emmanuel J. Candès Carlos Sing‐Long Joshua D. Trzasko	8
+ PDF Chat	A Singular Value Thresholding Algorithm for Matrix Completion	2010	Jian‐Feng Cai Emmanuel J. Candès Zuowei Shen	8
+	What Is Meant by “Missing at Random”?	2013	Shaun R. Seaman John C. Galati Dan Jackson John B. Carlin	8
+ PDF Chat	Adaptive shrinkage of singular values	2015	Julie Josse Sylvain Sardy	8
+	A principal component method to impute missing values for mixed data	2014	Vincent Audigier François Husson Julie Josse	8
+	Analysis of Incomplete Multivariate Data	1997	Joseph L. Schafer	8
+	Variable selection and prediction with incomplete high-dimensional data	2016	Ying Liu Yuanjia Wang Yang Feng Melanie M. Wall	7
+	Simple structure in component analysis techniques for mixtures of qualitative and quantitative variables	1991	Henk A. L. Kiers	7
+	Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares	2014	Trevor Hastie Rahul Mazumder Jason Lee Reza Bosagh Zadeh	7
+ PDF Chat	The Adaptive Lasso and Its Oracle Properties	2006	Hui Zou	7
+ PDF Chat	R-miss-tastic: a unified platform for missing values methods and workflows	2022	Imke Mayer Aude Sportisse Julie Josse Nicholas Tierney Nathalie Villa‐Vialaneix	7
+	Model Averaging and Dimension Selection for the Singular Value Decomposition	2007	Peter D. Hoff	7
+ PDF Chat	Generalized random forests	2019	Susan Athey Julie Tibshirani Stefan Wager	7
+	Using EM to Obtain Asymptotic Variance-Covariance Matrices: The SEM Algorithm	1991	Xiao‐Li Meng Donald B. Rubin	7
+ PDF Chat	The Optimal Hard Threshold for Singular Values is <inline-formula> <tex-math notation="TeX">\(4/\sqrt {3}\) </tex-math></inline-formula>	2014	Matan Gavish David L. Donoho	7
+	<b>Amelia</b>II: A Program for Missing Data	2011	James Honaker Gary King Matthew Blackwell	7
+	Spatial Interaction and the Statistical Analysis of Lattice Systems	1974	Julian Besag	6
+	Matrix estimation by Universal Singular Value Thresholding	2014	Sourav Chatterjee	6
+ PDF Chat	Generalizing Evidence From Randomized Clinical Trials to Target Populations: The ACTG 320 Trial	2010	S. R. Cole Elizabeth A. Stuart	6
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	6
+ PDF Chat	Estimation and Inference of Heterogeneous Treatment Effects using Random Forests	2017	Stefan Wager Susan Athey	6
+ PDF Chat	Causal Inference for Statistics, Social, and Biomedical Sciences	2015	Guido W. Imbens Donald B. Rubin	6
+	On the consistency of supervised learning with missing values	2019	Julie Josse Nicolas Prost Erwan Scornet Gaël Varoquaux	6
+ PDF Chat	Inverse Probability Weighting with Missing Predictors of Treatment Assignment or Missingness	2014	Shaun R. Seaman Ian R. White	6
+ PDF Chat	Introduction to the Special Section on Missing Data	2018	Julie Josse Jerome P. Reiter	6
+ PDF Chat	Convergence of a stochastic approximation version of the EM algorithm	1999	Bernard Delyon Marc Lavielle Éric Moulines	6
+ PDF Chat	The Use of Propensity Scores to Assess the Generalizability of Results from Randomized Trials	2010	Elizabeth A. Stuart Stephen R. Cole Catherine P. Bradshaw Philip J. Leaf	6
+	denoiseR: A Package for Low Rank Matrix Estimation	2016	Julie Josse Sylvain Sardy Stefan Wager	5
+	An analysis and synthesis of multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis and other methods for quantifying categorical multivariate data	1985	Michel Tenenhaus Forrest W. Young	5
+ PDF Chat	On the distribution of the largest eigenvalue in principal components analysis	2001	Iain M. Johnstone	5
+	Cross-validation of component models: A critical look at current methods	2008	Rasmus Bro Karin Kjeldahl Age K. Smilde Henk A. L. Kiers	5