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Journal Abstract Search
795 related items for PubMed ID: 20085642
1. Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study. Marshall A, Altman DG, Royston P, Holder RL. BMC Med Res Methodol; 2010 Jan 19; 10():7. PubMed ID: 20085642 [Abstract] [Full Text] [Related]
9. Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. White IR, Carlin JB. Stat Med; 2010 Dec 10; 29(28):2920-31. PubMed ID: 20842622 [Abstract] [Full Text] [Related]
10. Heckman imputation models for binary or continuous MNAR outcomes and MAR predictors. Galimard JE, Chevret S, Curis E, Resche-Rigon M. BMC Med Res Methodol; 2018 Aug 31; 18(1):90. PubMed ID: 30170561 [Abstract] [Full Text] [Related]
13. Does pattern mixture modelling reduce bias due to informative attrition compared to fitting a mixed effects model to the available cases or data imputed using multiple imputation?: a simulation study. Welch CA, Sabia S, Brunner E, Kivimäki M, Shipley MJ. BMC Med Res Methodol; 2018 Aug 29; 18(1):89. PubMed ID: 30157752 [Abstract] [Full Text] [Related]
14. Multiple imputation methods for handling missing data in cost-effectiveness analyses that use data from hierarchical studies: an application to cluster randomized trials. Gomes M, Díaz-Ordaz K, Grieve R, Kenward MG. Med Decis Making; 2013 Nov 29; 33(8):1051-63. PubMed ID: 23913915 [Abstract] [Full Text] [Related]
15. Comparison of Imputation Strategies for Incomplete Longitudinal Data in Life-Course Epidemiology. Shaw C, Wu Y, Zimmerman SC, Hayes-Larson E, Belin TR, Power MC, Glymour MM, Mayeda ER. Am J Epidemiol; 2023 Nov 10; 192(12):2075-2084. PubMed ID: 37338987 [Abstract] [Full Text] [Related]
20. Outcome-sensitive multiple imputation: a simulation study. Kontopantelis E, White IR, Sperrin M, Buchan I. BMC Med Res Methodol; 2017 Jan 09; 17(1):2. PubMed ID: 28068910 [Abstract] [Full Text] [Related] Page: [Next] [New Search]