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Items: 1 to 20 of 174

1.

Statistical analysis of randomized trials in tobacco treatment: longitudinal designs with dichotomous outcome.

Hall SM, Delucchi KL, Velicer WF, Kahler CW, Ranger-Moore J, Hedeker D, Tsoh JY, Niaura R.

Nicotine Tob Res. 2001 Aug;3(3):193-202.

PMID:
11506764
2.

Comparison of alternative strategies for analysis of longitudinal trials with dropouts.

Liu G, Gould AL.

J Biopharm Stat. 2002 May;12(2):207-26.

PMID:
12413241
3.

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
4.

Move over LOCF: principled methods for handling missing data in sleep disorder trials.

Olsen MK, Stechuchak KM, Edinger JD, Ulmer CS, Woolson RF.

Sleep Med. 2012 Feb;13(2):123-32. doi: 10.1016/j.sleep.2011.09.007. Epub 2011 Dec 14. Review.

PMID:
22172964
5.

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
6.

Attrition in longitudinal studies. How to deal with missing data.

Twisk J, de Vente W.

J Clin Epidemiol. 2002 Apr;55(4):329-37.

PMID:
11927199
8.

Estimating treatment efficacy over time: a logistic regression model for binary longitudinal outcomes.

Choi L, Dominici F, Zeger SL, Ouyang P.

Stat Med. 2005 Sep 30;24(18):2789-805.

PMID:
16134133
9.

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
10.

Analysis of longitudinal binary data with missing data due to dropouts.

Ali MW, Talukder E.

J Biopharm Stat. 2005;15(6):993-1007.

PMID:
16279357
11.

An overview of practical approaches for handling missing data in clinical trials.

DeSouza CM, Legedza AT, Sankoh AJ.

J Biopharm Stat. 2009 Nov;19(6):1055-73. doi: 10.1080/10543400903242795. Review.

PMID:
20183464
12.

Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials.

Jones AP, Riley RD, Williamson PR, Whitehead A.

Clin Trials. 2009 Feb;6(1):16-27. doi: 10.1177/1740774508100984. Erratum in: Clin Trials. 2009 Jun;6(3):288.

PMID:
19254930
13.

Power analyses for longitudinal study designs with missing data.

Tu XM, Zhang J, Kowalski J, Shults J, Feng C, Sun W, Tang W.

Stat Med. 2007 Jul 10;26(15):2958-81.

PMID:
17154250
14.

Mixed effects logistic regression models for longitudinal binary response data with informative drop-out.

Ten Have TR, Kunselman AR, Pulkstenis EP, Landis JR.

Biometrics. 1998 Mar;54(1):367-83.

PMID:
9544529
15.

Statistical methods for longitudinal research on bipolar disorders.

Hennen J.

Bipolar Disord. 2003 Jun;5(3):156-68. Review.

PMID:
12780870
16.

Incomplete quality of life data in randomized trials: missing forms.

Curran D, Molenberghs G, Fayers PM, Machin D.

Stat Med. 1998 Mar 15-Apr 15;17(5-7):697-709. Review.

PMID:
9549817
17.
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19.

Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives.

Brookes ST, Whitley E, Peters TJ, Mulheran PA, Egger M, Davey Smith G.

Health Technol Assess. 2001;5(33):1-56. Review.

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