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Items: 1 to 20 of 201

1.

Accounting for dropout bias using mixed-effects models.

Mallinckrodt CH, Clark WS, David SR.

J Biopharm Stat. 2001 Feb-May;11(1-2):9-21.

PMID:
11459446
2.

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
3.

MMRM versus MI in dealing with missing data--a comparison based on 25 NDA data sets.

Siddiqui O.

J Biopharm Stat. 2011 May;21(3):423-36. doi: 10.1080/10543401003777995.

PMID:
21442517
4.

A bias correction in testing treatment efficacy under informative dropout in clinical trials.

Kong F, Chen YF, Jin K.

J Biopharm Stat. 2009 Nov;19(6):980-1000. doi: 10.1080/10543400903242753.

PMID:
20183460
6.

MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets.

Siddiqui O, Hung HM, O'Neill R.

J Biopharm Stat. 2009;19(2):227-46. doi: 10.1080/10543400802609797.

PMID:
19212876
7.
9.

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 8;4:26.

10.

How should we deal with missing data in clinical trials involving Alzheimer's disease patients?

Coley N, Gardette V, Cantet C, Gillette-Guyonnet S, Nourhashemi F, Vellas B, Andrieu S.

Curr Alzheimer Res. 2011 Jun;8(4):421-33.

PMID:
21244348
11.

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
12.
13.
14.

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
15.

Last-observation-carried-forward imputation method in clinical efficacy trials: review of 352 antidepressant studies.

Woolley SB, Cardoni AA, Goethe JW.

Pharmacotherapy. 2009 Dec;29(12):1408-16. doi: 10.1592/phco.29.12.1408. Review.

PMID:
19947800
16.

Semi-parametric and non-parametric methods for clinical trials with incomplete data.

O'Brien PC, Zhang D, Bailey KR.

Stat Med. 2005 Feb 15;24(3):341-58. Erratum in: Stat Med. 2005 Nov 15;24(21):3385.

PMID:
15547952
17.

Assessing and interpreting treatment effects in longitudinal clinical trials with missing data.

Mallinckrodt CH, Sanger TM, Dubé S, DeBrota DJ, Molenberghs G, Carroll RJ, Potter WZ, Tollefson GD.

Biol Psychiatry. 2003 Apr 15;53(8):754-60.

PMID:
12706959
18.

Assessing response profiles from incomplete longitudinal clinical trial data under regulatory considerations.

Mallinckrodt CH, Clark SW, Carroll RJ, Molenbergh G.

J Biopharm Stat. 2003 May;13(2):179-90.

PMID:
12729388
19.

Intent-to-treat analysis for longitudinal clinical trials: coping with the challenge of missing values.

Mazumdar S, Liu KS, Houck PR, Reynolds CF 3rd.

J Psychiatr Res. 1999 Mar-Apr;33(2):87-95.

PMID:
10221740
20.

Numbers-needed-to-treat analyses--do timing, dropouts, and outcome matter? Pooled analysis of two randomized, placebo-controlled chronic low back pain trials.

Moore RA, Smugar SS, Wang H, Peloso PM, Gammaitoni A.

Pain. 2010 Dec;151(3):592-7. doi: 10.1016/j.pain.2010.07.013.

PMID:
20810214

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