404 related articles for article (PubMed ID: 29978944)
1. Effect of heteroscedasticity between treatment groups on mixed-effects models for repeated measures.
Gosho M; Maruo K
Pharm Stat; 2018 Sep; 17(5):578-592. PubMed ID: 29978944
[TBL] [Abstract][Full Text] [Related]
2. Comparison of bias-corrected covariance estimators for MMRM analysis in longitudinal data with dropouts.
Gosho M; Hirakawa A; Noma H; Maruo K; Sato Y
Stat Methods Med Res; 2017 Oct; 26(5):2389-2406. PubMed ID: 26265765
[TBL] [Abstract][Full Text] [Related]
3. The analysis of very small samples of repeated measurements I: an adjusted sandwich estimator.
Skene SS; Kenward MG
Stat Med; 2010 Nov; 29(27):2825-37. PubMed ID: 20839367
[TBL] [Abstract][Full Text] [Related]
4. A note on the bias of standard errors when orthogonality of mean and variance parameters is not satisfied in the mixed model for repeated measures analysis.
Maruo K; Ishii R; Yamaguchi Y; Doi M; Gosho M
Stat Med; 2020 Apr; 39(9):1264-1274. PubMed ID: 31916260
[TBL] [Abstract][Full Text] [Related]
5. The effect of correlation structure on treatment contrasts estimated from incomplete clinical trial data with likelihood-based repeated measures compared with last observation carried forward ANOVA.
Mallinckrodt CH; Kaiser CJ; Watkin JG; Molenberghs G; Carroll RJ
Clin Trials; 2004; 1(6):477-89. PubMed ID: 16279288
[TBL] [Abstract][Full Text] [Related]
6. Closed-form REML estimators and sample size determination for mixed effects models for repeated measures under monotone missingness.
Tang Y
Stat Med; 2017 Jun; 36(13):2135-2147. PubMed ID: 28226391
[TBL] [Abstract][Full Text] [Related]
7. Single time point comparisons in longitudinal randomized controlled trials: power and bias in the presence of missing data.
Ashbeck EL; Bell ML
BMC Med Res Methodol; 2016 Apr; 16():43. PubMed ID: 27068578
[TBL] [Abstract][Full Text] [Related]
8. Evaluation of overall treatment effect in MMRM.
Song T; Dong Q; Sankoh AJ; Molenberghs G
J Biopharm Stat; 2013; 23(6):1281-93. PubMed ID: 24138432
[TBL] [Abstract][Full Text] [Related]
9. Handling drop-out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches.
Lane P
Pharm Stat; 2008; 7(2):93-106. PubMed ID: 17351897
[TBL] [Abstract][Full Text] [Related]
10. On the multiple imputation variance estimator for control-based and delta-adjusted pattern mixture models.
Tang Y
Biometrics; 2017 Dec; 73(4):1379-1387. PubMed ID: 28407203
[TBL] [Abstract][Full Text] [Related]
11. The mixed model for repeated measures for cluster randomized trials: a simulation study investigating bias and type I error with missing continuous data.
Bell ML; Rabe BA
Trials; 2020 Feb; 21(1):148. PubMed ID: 32033617
[TBL] [Abstract][Full Text] [Related]
12. The analysis of very small samples of repeated measurements II: a modified Box correction.
Skene SS; Kenward MG
Stat Med; 2010 Nov; 29(27):2838-56. PubMed ID: 20860066
[TBL] [Abstract][Full Text] [Related]
13. The efficacy of duloxetine: a comprehensive summary of results from MMRM and LOCF_ANCOVA in eight clinical trials.
Mallinckrodt CH; Raskin J; Wohlreich MM; Watkin JG; Detke MJ
BMC Psychiatry; 2004 Sep; 4():26. PubMed ID: 15355546
[TBL] [Abstract][Full Text] [Related]
14. MMRM vs joint modeling of longitudinal responses and time to study drug discontinuation in clinical trials using a "de jure" estimand.
García-Hernandez A; Pérez T; Pardo MDC; Rizopoulos D
Pharm Stat; 2020 Nov; 19(6):909-927. PubMed ID: 32725810
[TBL] [Abstract][Full Text] [Related]
15. Kenward-Roger-type corrections for inference methods of network meta-analysis and meta-regression.
Noma H; Hamura Y; Gosho M; Furukawa TA
Res Synth Methods; 2023 Sep; 14(5):731-741. PubMed ID: 37399845
[TBL] [Abstract][Full Text] [Related]
16. Accounting for dropout bias using mixed-effects models.
Mallinckrodt CH; Clark WS; David SR
J Biopharm Stat; 2001; 11(1-2):9-21. PubMed ID: 11459446
[TBL] [Abstract][Full Text] [Related]
17. Consideration of the adaptive randomization allocation ratio in the presence of treatment group heteroscedasticity in clinical trials.
Lu J; Chen YF
J Biopharm Stat; 2022 May; 32(3):511-526. PubMed ID: 35695576
[TBL] [Abstract][Full Text] [Related]
18. An application of the mixed-effects model and pattern mixture model to treatment groups with differential missingness suspected not-missing-at-random.
Gosho M; Maruo K
Pharm Stat; 2021 Jan; 20(1):93-108. PubMed ID: 33249763
[TBL] [Abstract][Full Text] [Related]
19. Improving the mixed model for repeated measures to robustly increase precision in randomized trials.
Wang B; Du Y
Int J Biostat; 2023 Nov; ():. PubMed ID: 38016707
[TBL] [Abstract][Full Text] [Related]
20. A comparison of bias-corrected covariance estimators for generalized estimating equations.
Fan C; Zhang D; Zhang CH
J Biopharm Stat; 2013; 23(5):1172-87. PubMed ID: 23957522
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
