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Accounting for missing data in statistical analyses: multiple imputation is not always the answer

International journal of epidemiology, 2019-08, Vol.48 (4), p.1294-1304

2019

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Statistical Methods for Handling Incomplete Data

Second edition., 2021

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Missing Data in Clinical Studies

1. Aufl., 2007

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Dark Data: Why What You Don't Know Matters

Hand, David J

1, 2020

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Causal Inference: A Missing Data Perspective

Statistical science, 2018-05, Vol.33 (2), p.214-237

2018

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Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network

IEEE transactions on geoscience and remote sensing, 2018-08, Vol.56 (8), p.4274-4288

2018

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Multiple Imputation for Multilevel Data with Continuous and Binary Variables

Statistical science, 2018-05, Vol.33 (2), p.160-183

2018

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Modelless Data Quality Improvement of Streaming Synchrophasor Measurements by Exploiting the Low-Rank Hankel Structure

IEEE transactions on power systems, 2018-11, Vol.33 (6), p.6966-6977

2018

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An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications

IEEE transactions on industrial informatics, 2018-05, Vol.14 (5), p.2011-2022

2018

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A comparison of multiple imputation methods for missing data in longitudinal studies

BMC medical research methodology, 2018-12, Vol.18 (1), p.168-168, Article 168

2018

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A genetic algorithm for multivariate missing data imputation

Information sciences, 2023-01, Vol.619, p.947-967

2023

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Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis

Journal of clinical epidemiology, 2013-09, Vol.66 (9), p.1022-1028

2013

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Multiple Imputation in Practice: With Examples Using IVEware

2, 2018

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Advances in Bayesian Model Fit Evaluation for Structural Equation Models

Structural equation modeling, 2021-01, Vol.28 (1), p.1-14

2021

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Multiple Imputation: A Review of Practical and Theoretical Findings

Statistical science, 2018-05, Vol.33 (2), p.142-159

Murray, Jared S.

2018

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Dealing with missing data in multi-informant studies: A comparison of approaches

Behavior research methods, 2024-02

2024

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Estimation of missing values in heterogeneous traffic data: Application of multimodal deep learning model

Knowledge-based systems, 2020-04, Vol.194, p.105592, Article 105592

2020

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Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction

BMC medical research methodology, 2020-07, Vol.20 (1), p.199-199, Article 199

2020

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A Comprehensive Survey on Imputation of Missing Data in Internet of Things

ACM computing surveys, 2023-07, Vol.55 (7), p.1-38

2023

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PMU Missing Data Recovery Using Tensor Decomposition

IEEE transactions on power systems, 2020-11, Vol.35 (6), p.4554-4563

2020

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Inference of the distribution of fitness effects of mutations is affected by single nucleotide polymorphism filtering methods, sample size and population structure

Molecular ecology resources, 2023-10, Vol.23 (7), p.1589-1603

2023

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Multivariate longitudinal data analysis with censored and intermittent missing responses

Statistics in medicine, 2018-08, Vol.37 (19), p.2822-2835

2018

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Evaluating the state of the art in missing data imputation for clinical data

Briefings in bioinformatics, 2022-01, Vol.23 (1)

Luo, Yuan

2022

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Evaluating missing value imputation methods for food composition databases

Food and chemical toxicology, 2020-07, Vol.141, p.111368-111368, Article 111368

2020

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SICE: an improved missing data imputation technique

Journal of big data, 2020-06, Vol.7 (1), p.37-37, Article 37

2020

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Accounting for missing data in statistical analyses: multiple imputation is not always the answer

Statistical Methods for Handling Incomplete Data

Missing Data in Clinical Studies

Dark Data: Why What You Don't Know Matters

Causal Inference: A Missing Data Perspective

Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network

Multiple Imputation for Multilevel Data with Continuous and Binary Variables

Modelless Data Quality Improvement of Streaming Synchrophasor Measurements by Exploiting the Low-Rank Hankel Structure

An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications

A comparison of multiple imputation methods for missing data in longitudinal studies

A genetic algorithm for multivariate missing data imputation

Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis

Multiple Imputation in Practice: With Examples Using IVEware

Advances in Bayesian Model Fit Evaluation for Structural Equation Models

Multiple Imputation: A Review of Practical and Theoretical Findings

Dealing with missing data in multi-informant studies: A comparison of approaches

Estimation of missing values in heterogeneous traffic data: Application of multimodal deep learning model

Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction

A Comprehensive Survey on Imputation of Missing Data in Internet of Things

PMU Missing Data Recovery Using Tensor Decomposition

Inference of the distribution of fitness effects of mutations is affected by single nucleotide polymorphism filtering methods, sample size and population structure

Multivariate longitudinal data analysis with censored and intermittent missing responses

Evaluating the state of the art in missing data imputation for clinical data

Evaluating missing value imputation methods for food composition databases

SICE: an improved missing data imputation technique

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