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This paper reviews recent advances in missing data research using graphical models to represent multivariate dependencies.
Missing data in regression analysis
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Non-response models for the analysis of non-monotone non-ignorable missing data
Robins, J. M. (1997) · 1997
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Semiparametric regression for repeated outcomes with nonignorable nonresponse
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Identifiability in causal bayesian networks: A sound and complete algorithm
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Robust estimation in sequentially ignorable missing data and causal inference models
Robins, J. M. (2000) · 1999
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Adjusting for nonignorable drop-out using semiparametric nonresponse models
Scharfstein, D. O., A. Rotnitzky, and J. M. Robins (1999) · 1999
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Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models
Robins, J. M., A. Rotnitzky, and D. O. Scharfstein (2000) · 2000
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A comparison of inclusive and restrictive strategies in modern missing data procedures
Collins, L. M., J. L. Schafer, and C.-M. Kam (2001) · 2001
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Causal inference from graphical models
Lauritzen, S. L. (2001) · 2001
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Missing data series: Quantitative applications in the social sciences
Allison, P. (2002) · 2002
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Statistical analysis with missing data
Little, R. and D. Rubin (2002) · 2002
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A primer for the estimation of structural equation models in the presence of missing data: Maximum likelihood algorithms
Peters, C. L. O. and C. Enders (2002) · 2002
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Dealing with missing data
Scheffer, J. (2002) · 2002
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On the testable implications of causal models with hidden variables
Tian, J. and J. Pearl (2002) · 2002
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Missing data techniques for structural equation modeling
Allison, P. D. (2003) · 2003
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Doubly robust estimation in missing data and causal inference models
Bang, H. and J. M. Robins (2005) · 2005
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Applied multivariate research: Design and interpretation
Meyers, L. S., G. Gamst, and A. J. Guarino (2006) · 2006
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Can one assess whether missing data are missing at random in medical studies?
Potthoff, R., G. Tudor, K. Pieper, and V. Hasselblad (2006) · 2006
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Identification of conditional interventional distributions
Shpitser, I. and J. Pearl (2006) · 2006
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Researching complementary and alternative medicine
Adams, J. (2007) · 2007
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Graphical causal models
Elwert, F. (2013) · 2013
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On weighting approaches for missing data
Li, L., C. Shen, X. Li, and J. M. Robins (2013) · 2013
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Graphical models for inference with missing data
Mohan, K., J. Pearl, and J. Tian (2013) · 2013
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What is meant by “missing at random”?
Seaman, S., J. Galati, D. Jackson, J. Carlin, et al. (2013) · 2013
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Selection of auxiliary variables in missing data problems: Not all auxiliary variables are created equal
Thoemmes, F. and N. Rose (2013) · 2013
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Improving upon the efficiency of complete case analysis when covariates are mnar
Bartlett, J. W., J. R. Carpenter, K. Tilling, and S. Vansteelandt (2014) · 2014
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Missing data in randomised controlled trials–a practical guide. 2007
Carpenter, J. and M. Kenward (2014) · 2007
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Measuring and testing dependence by correlation of distances
Székely, G. J., M. L. Rizzo, N. K. Bakirov, et al. (2007) · 2007
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Generalized estimating equations for longitudinal data analysis
Fitzmaurice, G., G. Molenberghs, M. Davidian, and G. Verbeke (2008) · 2008
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Modeling and reasoning with Bayesian networks
Darwiche, A. (2009) · 2009
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Missing data analysis: Making it work in the real world
Graham, J. W. (2009) · 2009
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Probabilistic graphical models: principles and techniques
Koller, D. and N. Friedman (2009) · 2009
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Measurement bias and effect restoration in causal inference
Kuroki, M. and J. Pearl (2014) · 2014
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Statistical analysis with missing data
Little, R. and D. Rubin (2014) · 2014
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An efficient method for bayesian network parameter learning from incomplete data
Mohan, K., G. Van den Broeck, A. Choi, and J. Pearl (2014) · 2014
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Best practices in logistic regression
Osborne, J. W. (2014) · 2014
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External validity: From do-calculus to transportability across populations
Pearl, J. and E. Bareinboim (2014) · 2014
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Nonrespondent subsample multiple imputation in two-phase sampling for nonresponse
Zhang, N., H. Chen, and M. R. Elliott (2016) · 2014
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Asymptotically unbiased estimation of exposure odds ratios in complete records logistic regression
Bartlett, J. W., O. Harel, and J. R. Carpenter (2015) · 2015
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Modern adaptive randomized clinical trials: statistical and practical aspects
Sverdlov, O. (2015) · 2015
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Graphical representation of missing data problems
Thoemmes, F. and K. Mohan (2015) · 2015
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Efficient algorithms for bayesian network parameter learning from incomplete data
Van den Broeck, G., K. Mohan, A. Choi, A. Darwiche, and J. Pearl (2015) · 2015
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An incremental algorithm for repairing training sets with missing values
van Stein, B. and W. Kowalczyk (2016) · 2016
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Diagnosing missing always at random in multivariate data
Bojinov, I., N. Pillai, and D. Rubin (2017) · 2017
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A practical example demonstrating the utility of single-world intervention graphs
Breskin, A., S. R. Cole, and M. G. Hudgens (2018) · 2018
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On the utility of causal diagrams in modeling attrition: a practical example
Cinelli, C. and J. Pearl (2018) · 2018
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Missing data: a unified taxonomy guided by conditional independence
Doretti, M., S. Geneletti, and E. Stanghellini (2018) · 2018
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Estimated mortality on hiv treatment among active patients and patients lost to follow-up in 4 provinces of zambia: Findings from a multistage sampling-based survey
Holmes, C. B., I. Sikazwe, K. Sikombe, I. Eshun-Wilson, N. Czaicki, L. K. Beres, N. Mukamba, S. Simbeza, C. B. Moore, C. Hantuba, et al. (2018) · 2018
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On handling self-masking and other hard missing data problems
Mohan, K. (2018) · 2018
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