291 related articles for article (PubMed ID: 34788362)
21. Review and evaluation of imputation methods for multivariate longitudinal data with mixed-type incomplete variables.
Cao Y; Allore H; Vander Wyk B; Gutman R
Stat Med; 2022 Dec; 41(30):5844-5876. PubMed ID: 36220138
[TBL] [Abstract][Full Text] [Related]
22. Imputation of missing values of tumour stage in population-based cancer registration.
Eisemann N; Waldmann A; Katalinic A
BMC Med Res Methodol; 2011 Sep; 11():129. PubMed ID: 21929796
[TBL] [Abstract][Full Text] [Related]
23. 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; 18(1):90. PubMed ID: 30170561
[TBL] [Abstract][Full Text] [Related]
24. Robust imputation method with context-aware voting ensemble model for management of water-quality data.
Choi J; Lim KJ; Ji B
Water Res; 2023 Sep; 243():120369. PubMed ID: 37499538
[TBL] [Abstract][Full Text] [Related]
25. 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.
De Silva AP; Moreno-Betancur M; De Livera AM; Lee KJ; Simpson JA
BMC Med Res Methodol; 2017 Jul; 17(1):114. PubMed ID: 28743256
[TBL] [Abstract][Full Text] [Related]
26. [How to deal with missing data? Multiple imputation by chained equations: recommendations and explanations for clinical practice].
Legendre B; Cerasuolo D; Dejardin O; Boyer A
Nephrol Ther; 2023 Jun; 19(3):171-179. PubMed ID: 37272826
[TBL] [Abstract][Full Text] [Related]
27. Solving the many-variables problem in MICE with principal component regression.
Costantini E; Lang KM; Sijtsma K; Reeskens T
Behav Res Methods; 2024 Mar; 56(3):1715-1737. PubMed ID: 37540467
[TBL] [Abstract][Full Text] [Related]
28. Method for Incomplete and Imbalanced Data Based on Multivariate Imputation by Chained Equations and Ensemble Learning.
Li J; Wang Z; Wu L; Qiu S; Zhao H; Lin F; Zhang K
IEEE J Biomed Health Inform; 2024 May; 28(5):3102-3113. PubMed ID: 38483807
[TBL] [Abstract][Full Text] [Related]
29. Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data.
Resche-Rigon M; White IR; Bartlett JW; Peters SA; Thompson SG;
Stat Med; 2013 Dec; 32(28):4890-905. PubMed ID: 23857554
[TBL] [Abstract][Full Text] [Related]
30. 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; 192(12):2075-2084. PubMed ID: 37338987
[TBL] [Abstract][Full Text] [Related]
31. Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data.
Mir AA; Kearfott KJ; Çelebi FV; Rafique M
PLoS One; 2022; 17(1):e0262131. PubMed ID: 35025953
[TBL] [Abstract][Full Text] [Related]
32. A stacked approach for chained equations multiple imputation incorporating the substantive model.
Beesley LJ; Taylor JMG
Biometrics; 2021 Dec; 77(4):1342-1354. PubMed ID: 32920819
[TBL] [Abstract][Full Text] [Related]
33. Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study.
De Silva AP; Moreno-Betancur M; De Livera AM; Lee KJ; Simpson JA
BMC Med Res Methodol; 2019 Jan; 19(1):14. PubMed ID: 30630434
[TBL] [Abstract][Full Text] [Related]
34. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.
Seaman SR; Hughes RA
Stat Methods Med Res; 2018 Jun; 27(6):1603-1614. PubMed ID: 27597798
[TBL] [Abstract][Full Text] [Related]
35. Accounting for not-at-random missingness through imputation stacking.
Beesley LJ; Taylor JMG
Stat Med; 2021 Nov; 40(27):6118-6132. PubMed ID: 34459011
[TBL] [Abstract][Full Text] [Related]
36. Empirical Comparison of Imputation Methods for Multivariate Missing Data in Public Health.
Pan S; Chen S
Int J Environ Res Public Health; 2023 Jan; 20(2):. PubMed ID: 36674279
[TBL] [Abstract][Full Text] [Related]
37. Dealing with missing delirium assessments in prospective clinical studies of the critically ill: a simulation study and reanalysis of two delirium studies.
Raman R; Chen W; Harhay MO; Thompson JL; Ely EW; Pandharipande PP; Patel MB
BMC Med Res Methodol; 2021 May; 21(1):97. PubMed ID: 33952189
[TBL] [Abstract][Full Text] [Related]
38. Imputing missing covariates in time-to-event analysis within distributed research networks: A simulation study.
Li D; Wong J; Li X; Toh S; Wang R
Pharmacoepidemiol Drug Saf; 2023 Mar; 32(3):330-340. PubMed ID: 36380400
[TBL] [Abstract][Full Text] [Related]
39. Multiple imputation for longitudinal data using Bayesian lasso imputation model.
Yamaguchi Y; Yoshida S; Misumi T; Maruo K
Stat Med; 2022 Mar; 41(6):1042-1058. PubMed ID: 35064581
[TBL] [Abstract][Full Text] [Related]
40. Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation.
Enders CK; Mistler SA; Keller BT
Psychol Methods; 2016 Jun; 21(2):222-40. PubMed ID: 26690775
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
