A comparison of multiple imputation methods for missing data in longitudinal studies
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Md Hamidul Huque | John B Carlin | Julie A Simpson | Katherine J Lee | Katherine J. Lee | J. Carlin | J. Simpson
[1] Jaakko Nevalainen,et al. Missing values in longitudinal dietary data: A multiple imputation approach based on a fully conditional specification , 2009, Statistics in medicine.
[2] James R Carpenter,et al. Joint modelling rationale for chained equations , 2014, BMC Medical Research Methodology.
[3] J. Ziviani,et al. Speech and Language Difficulties Along with Other Child and Family Factors Associated with Health Related Quality of Life of Australian Children , 2016 .
[4] Shaun R Seaman,et al. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model , 2016, Statistical methods in medical research.
[5] Harvey Goldstein,et al. Multilevel models with multivariate mixed response types , 2009 .
[6] Joseph L Schafer,et al. Analysis of Incomplete Multivariate Data , 1997 .
[7] Recai M. Yucel,et al. Performance of Sequential Imputation Method in Multilevel Applications , 2009 .
[8] Alexander Robitzsch,et al. Some Additional Multiple Imputation Functions, Especially for'mice' , 2015 .
[9] Matthieu Resche-Rigon,et al. Multiple imputation by chained equations for systematically and sporadically missing multilevel data , 2018, Statistical methods in medical research.
[10] N M Laird,et al. Missing data in longitudinal studies. , 1988, Statistics in medicine.
[11] M. Wake,et al. Bidirectional associations between overweight and health-related quality of life from 4–11 years: Longitudinal Study of Australian Children , 2013, International Journal of Obesity.
[12] Harvey Goldstein,et al. REALCOM-IMPUTE Software for Multilevel Multiple Imputation with Mixed Response Types , 2011 .
[13] Qi Long,et al. Multiple imputation in the presence of high-dimensional data , 2016, Statistical methods in medical research.
[14] T. Cole,et al. Establishing a standard definition for child overweight and obesity worldwide: international survey , 2000, BMJ : British Medical Journal.
[15] S. van Buuren. Multiple imputation of discrete and continuous data by fully conditional specification , 2007, Statistical methods in medical research.
[16] D. Rubin,et al. Statistical Analysis with Missing Data , 1988 .
[17] D. Rubin,et al. Fully conditional specification in multivariate imputation , 2006 .
[18] Anurika Priyanjali De Silva,et al. A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study , 2017, BMC Medical Research Methodology.
[19] J. Schafer,et al. Computational Strategies for Multivariate Linear Mixed-Effects Models With Missing Values , 2002 .
[20] Joseph L Schafer,et al. Robustness of a multivariate normal approximation for imputation of incomplete binary data , 2007, Statistics in medicine.
[21] Patrick Royston,et al. Tuning multiple imputation by predictive mean matching and local residual draws , 2014, BMC Medical Research Methodology.
[22] A. Copas,et al. A comparison of multiple‐imputation methods for handling missing data in repeated measurements observational studies , 2016 .
[23] M. Wake,et al. Bi-directional longitudinal associations between overweight and health-related quality of life from 4–11years. Longitudinal study of Australian children. , 2014, Appetite.
[24] Craig K Enders,et al. A Fully Conditional Specification Approach to Multilevel Imputation of Categorical and Continuous Variables , 2018, Psychological methods.
[25] J. R. Carpenter,et al. Multiple imputation for IPD meta‐analysis: allowing for heterogeneity and studies with missing covariates , 2015, Statistics in medicine.
[26] Ian R White,et al. Evaluation of two-fold fully conditional specification multiple imputation for longitudinal electronic health record data , 2014, Statistics in medicine.
[27] Stef van Buuren,et al. MICE: Multivariate Imputation by Chained Equations in R , 2011 .
[28] Jared S. Murray,et al. Multiple Imputation: A Review of Practical and Theoretical Findings , 2018, 1801.04058.
[29] J. Ware,et al. Applied Longitudinal Analysis , 2004 .
[30] John Van Hoewyk,et al. A multivariate technique for multiply imputing missing values using a sequence of regression models , 2001 .
[31] Panteha Hayati Rezvan,et al. A review of the reporting and implementation of multiple imputation in medical research , 2015 .
[32] John B Carlin,et al. American Journal of Epidemiology Practice of Epidemiology Multiple Imputation for Missing Data: Fully Conditional Specification versus Multivariate Normal Imputation , 2022 .
[33] Nicholas J. Horton,et al. A Potential for Bias When Rounding in Multiple Imputation , 2003 .
[34] Vincent Audigier,et al. Multiple Imputation for Multilevel Data with Continuous and Binary Variables , 2017, 1702.00971.
[35] P. Diggle,et al. Analysis of Longitudinal Data. , 1997 .
[36] M. Kenward,et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls , 2009, BMJ : British Medical Journal.
[37] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[38] Craig K Enders,et al. Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation. , 2016, Psychological methods.
[39] Julie Josse,et al. Multiple imputation for continuous variables using a Bayesian principal component analysis† , 2014, 1401.5747.
[40] S. van Buuren,et al. Multiple Imputation of Multilevel Data , 2006 .
[41] Alexander Robitzsch,et al. Multiple Imputation of Missing Data in Multilevel Designs: A Comparison of Different Strategies , 2017, Psychological methods.