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Keyword

missing not at random

Description: A missing-data mechanism in which the probability that a value is missing depends on information not observed in the dataset.
OpenAlex ID: keywords/missing-not-at-random
Missing Data
2014 · Daniel A. Newman · Organizational Research Methods · 1,404
A survey on missing data in machine learning
2021 · Tlamelo Emmanuel, Thabiso Maupong, et al. · Journal Of Big Data · 1,059
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Missing data and multiple imputation in clinical epidemiological research
2017 · Alma Pedersen, Ellen Mikkelsen, et al. · Clinical Epidemiology · 986
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Regression with Missing X 's: A Review
1992 · Roderick J. A. Little · Journal of the American Statistical Association · 968
Accounting for missing data in statistical analyses: multiple imputation is not always the answer
2019 · Rachael A Hughes, Jon Heron, et al. · International Journal of Epidemiology · 799
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Random forest missing data algorithms
2017 · Fei Tang, Hemant Ishwaran · Statistical Analysis and Data Mining The ASA Data Science Journal · 779
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Loss to Follow-Up in Cohort Studies: How Much is Too Much?
2004 · Vicki Kristman, Michael Manno, et al. · European Journal of Epidemiology · 736
Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data
2018 · Runmin Wei, Jingye Wang, et al. · Scientific Reports · 711
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On the Joys of Missing Data
2013 · T. D. Little, T. D. Jorgensen, et al. · Journal of Pediatric Psychology · 680
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Dealing with missing data in a multi-question depression scale: a comparison of imputation methods
2006 · Fiona M Shrive, Heather Stuart, et al. · BMC Medical Research Methodology · 648
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Multiple Imputation
2015 · Peng Li, Elizabeth A. Stuart, et al. · JAMA · 623
Multiple imputation of missing values was not necessary before performing a longitudinal mixed-model analysis
2013 · Jos Twisk, Michiel de Boer, et al. · Journal of Clinical Epidemiology · 565
Analyzing incomplete longitudinal clinical trial data
2004 · G. Molenberghs · Biostatistics · 463
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Dealing With Missing Outcome Data in Randomized Trials and Observational Studies
2011 · Rolf H. H. Groenwold, A. Rogier T. Donders, et al. · American Journal of Epidemiology · 398
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Handling missing data in self-report measures
2005 · Susan M. Fox-Wasylyshyn, Maher M. El-Masri · Research in Nursing & Health · 396
Handling missing data in clinical research
2022 · Martijn W. Heymans, Jos W.R. Twisk · Journal of Clinical Epidemiology · 393
Training and testing of recommender systems on data missing not at random
2010 · Harald Steck · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 374
Recommendations for the Primary Analysis of Continuous Endpoints in Longitudinal Clinical Trials
2008 · Craig H. Mallinckrodt, Peter W. Lane, et al. · Drug Information Journal · 355
RETRACTED: Estrogen receptor-interacting protein that modulates its nongenomic activity-crosstalk with Src/Erk phosphorylation cascade
2002 · Chi-Wai Wong, Christopher McNally, et al. · Proceedings of the National Academy of Sciences · 324
Berkson's Bias, Selection Bias, and Missing Data
2011 · Daniel Westreich · Epidemiology · 322
Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback
2020 · Yuta Saito, Suguru Yaginuma, et al. · 301
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MMRM vs. LOCF: A Comprehensive Comparison Based on Simulation Study and 25 NDA Datasets
2009 · Ohidul Siddiqui, H. M. James Hung, et al. · Journal of Biopharmaceutical Statistics · 301
Practical and statistical issues in missing data for longitudinal patient-reported outcomes
2013 · Melanie L Bell, Diane L Fairclough · Statistical Methods in Medical Research · 285
A Primer on the Use of Modern Missing-Data Methods in Psychosomatic Medicine Research
2006 · Craig K. Enders · Psychosomatic Medicine · 274
Handling drop‐out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches
2007 · Peter Lane · Pharmaceutical Statistics · 262
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Works count: 1,731
Citation count: 31,690
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