These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
175 related articles for article (PubMed ID: 29129673)
1. Making an unknown unknown a known unknown: Missing data in longitudinal neuroimaging studies. Matta TH; Flournoy JC; Byrne ML Dev Cogn Neurosci; 2018 Oct; 33():83-98. PubMed ID: 29129673 [TBL] [Abstract][Full Text] [Related]
2. Analyzing longitudinal data with missing values. Enders CK Rehabil Psychol; 2011 Nov; 56(4):267-88. PubMed ID: 21967118 [TBL] [Abstract][Full Text] [Related]
3. On the joys of missing data. Little TD; Jorgensen TD; Lang KM; Moore EW J Pediatr Psychol; 2014 Mar; 39(2):151-62. PubMed ID: 23836191 [TBL] [Abstract][Full Text] [Related]
4. Attrition in longitudinal studies. How to deal with missing data. Twisk J; de Vente W J Clin Epidemiol; 2002 Apr; 55(4):329-37. PubMed ID: 11927199 [TBL] [Abstract][Full Text] [Related]
5. Missing data in longitudinal studies: cross-sectional multiple imputation provides similar estimates to full-information maximum likelihood. Ferro MA Ann Epidemiol; 2014 Jan; 24(1):75-7. PubMed ID: 24210708 [TBL] [Abstract][Full Text] [Related]
6. Estimation methods for marginal and association parameters for longitudinal binary data with nonignorable missing observations. Li H; Yi GY Stat Med; 2013 Feb; 32(5):833-48. PubMed ID: 22833460 [TBL] [Abstract][Full Text] [Related]
7. A structured framework for assessing sensitivity to missing data assumptions in longitudinal clinical trials. Mallinckrodt CH; Lin Q; Molenberghs M Pharm Stat; 2013; 12(1):1-6. PubMed ID: 23193075 [TBL] [Abstract][Full Text] [Related]
8. The impact of dichotomization in longitudinal data analysis: a simulation study. Yoo B Pharm Stat; 2010; 9(4):298-312. PubMed ID: 19904810 [TBL] [Abstract][Full Text] [Related]
9. Review of guidelines and literature for handling missing data in longitudinal clinical trials with a case study. Liu M; Wei L; Zhang J Pharm Stat; 2006; 5(1):7-18. PubMed ID: 17080924 [TBL] [Abstract][Full Text] [Related]
10. Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies. Guillaume B; Wang C; Poh J; Shen MJ; Ong ML; Tan PF; Karnani N; Meaney M; Qiu A Neuroimage; 2018 Jun; 173():57-71. PubMed ID: 29448075 [TBL] [Abstract][Full Text] [Related]
11. Responsiveness-informed multiple imputation and inverse probability-weighting in cohort studies with missing data that are non-monotone or not missing at random. Doidge JC Stat Methods Med Res; 2018 Feb; 27(2):352-363. PubMed ID: 26984909 [TBL] [Abstract][Full Text] [Related]
12. Using multiple imputation for analysis of incomplete data in clinical research. McCleary L Nurs Res; 2002; 51(5):339-43. PubMed ID: 12352784 [TBL] [Abstract][Full Text] [Related]
13. A comparison of power analysis methods for evaluating effects of a predictor on slopes in longitudinal designs with missing data. Wang C; Hall CB; Kim M Stat Methods Med Res; 2015 Dec; 24(6):1009-29. PubMed ID: 22357710 [TBL] [Abstract][Full Text] [Related]
14. Evaluation of Multi-parameter Test Statistics for Multiple Imputation. Liu Y; Enders CK Multivariate Behav Res; 2017; 52(3):371-390. PubMed ID: 28328291 [TBL] [Abstract][Full Text] [Related]
15. Likelihood methods for incomplete longitudinal binary responses with incomplete categorical covariates. Lipsitz SR; Ibrahim JG; Fitzmaurice GM Biometrics; 1999 Mar; 55(1):214-23. PubMed ID: 11318157 [TBL] [Abstract][Full Text] [Related]
16. Multiple imputation as a flexible tool for missing data handling in clinical research. Enders CK Behav Res Ther; 2017 Nov; 98():4-18. PubMed ID: 27890222 [TBL] [Abstract][Full Text] [Related]
17. Pseudo-likelihood methods for longitudinal binary data with non-ignorable missing responses and covariates. Parzen M; Lipsitz SR; Fitzmaurice GM; Ibrahim JG; Troxel A Stat Med; 2006 Aug; 25(16):2784-96. PubMed ID: 16345018 [TBL] [Abstract][Full Text] [Related]
18. Including auxiliary item information in longitudinal data analyses improved handling missing questionnaire outcome data. Eekhout I; Enders CK; Twisk JW; de Boer MR; de Vet HC; Heymans MW J Clin Epidemiol; 2015 Jun; 68(6):637-45. PubMed ID: 25724894 [TBL] [Abstract][Full Text] [Related]
19. Sensitivity analysis of incomplete longitudinal data departing from the missing at random assumption: Methodology and application in a clinical trial with drop-outs. Moreno-Betancur M; Chavance M Stat Methods Med Res; 2016 Aug; 25(4):1471-89. PubMed ID: 23698867 [TBL] [Abstract][Full Text] [Related]
20. Identifying reprioritization response shift in a stroke caregiver population: a comparison of missing data methods. Sajobi TT; Lix LM; Singh G; Lowerison M; Engbers J; Mayo NE Qual Life Res; 2015 Mar; 24(3):529-40. PubMed ID: 25344817 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]