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Items: 1 to 20 of 140

1.

Risk-stratified imputation in survival analysis.

Kennedy RE, Adragni KP, Tiwari HK, Voeks JH, Brott TG, Howard G.

Clin Trials. 2013 Aug;10(4):530-9. doi: 10.1177/1740774513493150. Epub 2013 Jul 1.

2.

Using audit information to adjust parameter estimates for data errors in clinical trials.

Shepherd BE, Shaw PA, Dodd LE.

Clin Trials. 2012 Dec;9(6):721-9. doi: 10.1177/1740774512450100. Epub 2012 Jul 30.

3.

Survival analysis using auxiliary variables via non-parametric multiple imputation.

Hsu CH, Taylor JM, Murray S, Commenges D.

Stat Med. 2006 Oct 30;25(20):3503-17.

PMID:
16345047
4.
5.

Estimating the effect of multiple imputation on incomplete longitudinal data with application to a randomized clinical study.

Fong DY, Rai SN, Lam KS.

J Biopharm Stat. 2013;23(5):1004-22. doi: 10.1080/10543406.2013.813514.

PMID:
23957512
6.

Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.

Salim A, Mackinnon A, Christensen H, Griffiths K.

Psychiatry Res. 2008 Sep 30;160(3):335-45. doi: 10.1016/j.psychres.2007.08.005. Epub 2008 Aug 20.

PMID:
18718673
7.

Estimation of colorectal adenoma recurrence with dependent censoring.

Hsu CH, Long Q, Alberts DS.

BMC Med Res Methodol. 2009 Sep 29;9:66. doi: 10.1186/1471-2288-9-66.

8.

Multiple imputation based on restricted mean model for censored data.

Liu LX, Murray S, Tsodikov A.

Stat Med. 2011 May 30;30(12):1339-50. doi: 10.1002/sim.4163. Epub 2011 Jan 11.

9.

Analysis of accelerated failure time data with dependent censoring using auxiliary variables via nonparametric multiple imputation.

Hsu CH, Taylor JM, Hu C.

Stat Med. 2015 Aug 30;34(19):2768-80. doi: 10.1002/sim.6534. Epub 2015 May 21.

10.

Multiple imputation for interval censored data with auxiliary variables.

Hsu CH, Taylor JM, Murray S, Commenges D.

Stat Med. 2007 Feb 20;26(4):769-81.

11.

Analyses of cumulative incidence functions via non-parametric multiple imputation.

Ruan PK, Gray RJ.

Stat Med. 2008 Nov 29;27(27):5709-24. doi: 10.1002/sim.3402.

PMID:
18712779
12.
13.
14.

Sensitivity analysis of progression-free survival with dependent withdrawal.

Ruan PK, Gray RJ.

Stat Med. 2008 Apr 15;27(8):1180-98.

PMID:
17768718
15.

Bias and Precision of the "Multiple Imputation, Then Deletion" Method for Dealing With Missing Outcome Data.

Sullivan TR, Salter AB, Ryan P, Lee KJ.

Am J Epidemiol. 2015 Sep 15;182(6):528-34. doi: 10.1093/aje/kwv100. Epub 2015 Sep 2.

PMID:
26337075
16.

A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis.

Wallace ML, Anderson SJ, Mazumdar S.

Stat Med. 2010 Dec 20;29(29):3004-16. doi: 10.1002/sim.4079. Epub 2010 Oct 20.

17.

Comparisons of methods for analysis of repeated binary responses with missing data.

Frank Liu G, Zhan X.

J Biopharm Stat. 2011 May;21(3):371-92. doi: 10.1080/10543401003687129.

PMID:
21442514
18.

Using cure models and multiple imputation to utilize recurrence as an auxiliary variable for overall survival.

Conlon AS, Taylor JM, Sargent DJ, Yothers G.

Clin Trials. 2011 Oct;8(5):581-90. doi: 10.1177/1740774511414741. Epub 2011 Sep 15.

19.

Handling missing quality of life data in HIV clinical trials: what is practical?

Fairclough DL, Thijs H, Huang IC, Finnern HW, Wu AW.

Qual Life Res. 2008 Feb;17(1):61-73. Epub 2007 Dec 11.

PMID:
18071926
20.

Comparison of imputation and modelling methods in the analysis of a physical activity trial with missing outcomes.

Wood AM, White IR, Hillsdon M, Carpenter J.

Int J Epidemiol. 2005 Feb;34(1):89-99. Epub 2004 Aug 27.

PMID:
15333619

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