Multiple Imputation for Nonresponse

By Jörg Drechsler. 2011

1,215 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Health Professions

View Paper: https://www.semanticscholar.org/paper/e59c2923dbe876b7f38f9499bee508860f619e09

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In General Health Professions

Citations in the corpus

Predicting Risk of Suicide Attempts Over Time Through Machine Learning (2017, methodology): “In general, we adhered to multiple imputation to address missingness in each iteration of the algorithm (Deeks, 2011; Harrell, 2006; Rubin, 2004).”
Efficient Quantile Regression Analysis With Missing Observations (2015, background): “Multiple imputation (Rubin 1987; Lipsitz et al. 1998; Aerts et al. 2002) is also widely used for remediating problems caused by incomplete data.”
Estimating Average Causal Effects Under Interference Between Units (2013, methodology): “A practical implementation of this procedure would be a multiple imputation approach: impute M random draws of the adjacency matrix from a random graph model, estimate causal effects on each, and then aggregate estimates with the usual multiple imputation combination formulas (Rubin, 1987).”
Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study (2020, methodology): “…chose this method because multiple imputation techniques are known to be more robust and better capable to account for uncertainty compared with single imputation ones [33] (as they employ the joint distribution of the available features), and MICE in particular can also handle diﬀerent data types.”
Causal inference with confounders missing not at random (2017, neutral): “Under this assumption, both the full data distribution and the causal effects are identiﬁable, and multiple imputation can be used to obtain estimates of the causal effects (Rubin, 1987; Qu & Lipkovich, 2009; Crowe et al., 2010; Mitra & Reiter, 2011; Seaman & White, 2014).”
Relation between language experiences in preschool classrooms and children's kindergarten and fourth-grade language and reading abilities. (2011, methodology): “Missing values were multiply imputed (Allison, 2001; Rubin, 1987) using the PROC MI procedure in SAS.”
Weighted Generalized Estimating Functions for Longitudinal Response and Covariate Data That Are Missing at Random (2010, methodology): “There are alternative popular approaches for dealing with missing response or covariate data, including the EM algorithm (Dempster, Laird, and Rubin 1977) and multiple imputation (Rubin 1987, 1996).”
Instrumental Variables: An Econometrician's Perspective (2014, neutral): “The statistics literature (Rubin, 1976, 1987, 1996; Little and Rubin, 1987) has primarily focused on models that assume that units with item nonresponse are comparable to units with complete response, conditional on covariates that are always observed.”
Machine Learning and Decision Support in Critical Care (2016, methodology): “…imputation, a technique which involves repeatedly imputing plausible values for missing data and averaging over many instances of imputation [108], [109], has received wide praise among the medical literature but has yet to gain traction in the critical care literature [99], though this is…”
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning (2019, methodology): “The ﬁrst component α ( x i , ¯ y ) follows a “Model the World” approach (Schafer, 1997; Rubin, 2004; Dud ´ ık et al., 2011), which exploits a model ˆ δ ( x, ¯ y ) of the reward.”
Spatial Panel-data Models Using Stata (2017, methodology): “In this way, both the coeﬃcients and the standard errors will be adjusted for the between-imputations variability according to the combination rules given in Rubin (1987).”
Rebutting Existing Misconceptions About Multiple Imputation as a Method for Handling Missing Data (2019, methodology): “However, many authors citing this paper state that according to Van Ginkel and Kroonenberg (2014a) combination rules for ANOVA are not available in SPSS, ignoring the fact that the very paper being referenced provides a solution in the form of an SPSS macro (see Van Ginkel & Kroonenberg, 2015, for a”
Predicting Academic Achievement and Attainment: The Contribution of Early Academic Skills, Attention Difficulties, and Social Competence (2016, methodology): “The model described in the next section was estimated for each imputed dataset and the results were combined (Rubin, 1987).”
Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks (2017, methodology): “Imputation methods [3, 4, 5, 6] attempt to reconstruct missing data by capturing the synchronous relationships across data streams but not the temporal relationships within streams.”
What is working memory capacity, and how can we measure it? (2013, methodology): “Estimating all models with these imputed data had only small effects on correlation and regression coefficients and had no impact on the conclusions drawn from the models. average of the SE and the estimated parameter variation between analyses using the formula of Rubin (1987).”