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Keyword

missing data mechanisms

Description: Statistical processes that describe how the probability of a value being missing relates to observed or unobserved data.
OpenAlex ID: keywords/missing-data-mechanisms
Missing data: Our view of the state of the art.
2002 · Joseph L. Schafer, John W. Graham · Psychological Methods · 11,622
Applied Missing Data Analysis
2010 · Craig K. Enders · 7,034
Missing Data Analysis: Making It Work in the Real World
2008 · John W. Graham · Annual Review of Psychology · 6,145
When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts
2017 · Janus Christian Jakobsen, Christian Gluud, et al. · BMC Medical Research Methodology · 2,736
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Doubly Robust Estimation in Missing Data and Causal Inference Models
2005 · Heejung Bang, James M. Robins · Biometrics · 1,969
The prevention and handling of the missing data
2013 · Hyun Kang · Korean Journal of Anesthesiology · 1,725
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How can I deal with missing data in my study?
2001 · Derrick A. Bennett · Australian and New Zealand Journal of Public Health · 1,648
Missing Data
2014 · Daniel A. Newman · Organizational Research Methods · 1,404
Fully conditional specification in multivariate imputation
2006 · S. Van Buuren, J. P.L. Brand, et al. · Journal of Statistical Computation and Simulation · 1,217
The Analysis of Social Science Data with Missing Values
1989 · RODERICK J. A. LITTLE, DONALD B. RUBIN · Sociological Methods & Research · 1,015
On Structural Equation Modeling with Data that are not Missing Completely at Random
1987 · Bengt Muthén, David Kaplan, et al. · Psychometrika · 882
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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Multiple Imputation for Missing Data: Fully Conditional Specification Versus Multivariate Normal Imputation
2010 · K. J. Lee, J. B. Carlin · American Journal of Epidemiology · 792
Missing Data: A Gentle Introduction
2007 · Patrick E. McKnight, Katherine McKnight, et al. · 782
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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Bias and efficiency of multiple imputation compared with complete‐case analysis for missing covariate values
2010 · Ian R. White, John B. Carlin · Statistics in Medicine · 745
Loss to Follow-Up in Cohort Studies: How Much is Too Much?
2004 · Vicki Kristman, Michael Manno, et al. · European Journal of Epidemiology · 736
On the Joys of Missing Data
2013 · T. D. Little, T. D. Jorgensen, et al. · Journal of Pediatric Psychology · 680
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A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials
2014 · Rita Faria, Manuel Gomes, et al. · PharmacoEconomics · 669
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Missing value imputation: a review and analysis of the literature (2006–2017)
2019 · Wei-Chao Lin, Chih-Fong Tsai · Artificial Intelligence Review · 609
Testing for Selectivity Bias in Panel Data Models
1992 · Marno Verbeek, Theo Nijman · International Economic Review · 562
Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis
2012 · Rolf H.H. Groenwold, Ian R. White, et al. · Canadian Medical Association Journal · 537
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Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies
2016 · Cosmin Lazar, Laurent Gatto, et al. · Journal of Proteome Research · 528
Missing data methods in longitudinal studies: a review
2009 · Joseph G. Ibrahim, Geert Molenberghs · Test · 514
Dealing with missing data
2002 · Judi Scheffer · Massey Research Online (Massey University) · 463
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Works count: 2,016
Citation count: 75,220
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