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Items: 1 to 20 of 101

1.

Bayesian hierarchical models combining different study types and adjusting for covariate imbalances: a simulation study to assess model performance.

McCarron CE, Pullenayegum EM, Thabane L, Goeree R, Tarride JE.

PLoS One. 2011;6(10):e25635. doi: 10.1371/journal.pone.0025635. Epub 2011 Oct 10.

2.
3.

Performance of analytical methods for overdispersed counts in cluster randomized trials: sample size, degree of clustering and imbalance.

Durán Pacheco G, Hattendorf J, Colford JM Jr, Mäusezahl D, Smith T.

Stat Med. 2009 Oct 30;28(24):2989-3011. doi: 10.1002/sim.3681.

PMID:
19672840
4.

Methods for covariate adjustment in cost-effectiveness analysis that use cluster randomised trials.

Gomes M, Grieve R, Nixon R, Ng ES, Carpenter J, Thompson SG.

Health Econ. 2012 Sep;21(9):1101-18. doi: 10.1002/hec.2812. Epub 2012 Mar 28.

PMID:
22461149
5.

Incorporating data from various trial designs into a mixed treatment comparison model.

Schmitz S, Adams R, Walsh C.

Stat Med. 2013 Jul 30;32(17):2935-49. doi: 10.1002/sim.5764. Epub 2013 Feb 25.

PMID:
23440610
6.

What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data.

Sweeting MJ, Sutton AJ, Lambert PC.

Stat Med. 2004 May 15;23(9):1351-75. Erratum in: Stat Med. 2006 Aug 15;25(15):2700.

PMID:
15116347
7.

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.

8.

Controlling ecological bias in evidence synthesis of trials reporting on collapsed and overlapping covariate categories.

Govan L, Ades AE, Weir CJ, Welton NJ, Langhorne P.

Stat Med. 2010 May 30;29(12):1340-56. doi: 10.1002/sim.3869.

PMID:
20191599
9.

A Bayesian adaptive blinded sample size adjustment method for risk differences.

Hartley AM.

Pharm Stat. 2015 Nov-Dec;14(6):488-514. doi: 10.1002/pst.1708. Epub 2015 Sep 24.

PMID:
26403845
10.

Bayesian response adaptive randomization using longitudinal outcomes.

Hatayama T, Morita S, Sakamaki K.

Pharm Stat. 2015 Sep-Oct;14(5):369-76. doi: 10.1002/pst.1695. Epub 2015 Jun 23.

PMID:
26099995
11.

Bayesian hierarchical modeling of patient subpopulations: efficient designs of Phase II oncology clinical trials.

Berry SM, Broglio KR, Groshen S, Berry DA.

Clin Trials. 2013 Oct;10(5):720-34. doi: 10.1177/1740774513497539. Epub 2013 Aug 27.

14.

Indirect comparisons of competing interventions.

Glenny AM, Altman DG, Song F, Sakarovitch C, Deeks JJ, D'Amico R, Bradburn M, Eastwood AJ; International Stroke Trial Collaborative Group.

Health Technol Assess. 2005 Jul;9(26):1-134, iii-iv.

15.

Bayesian methods in health technology assessment: a review.

Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR.

Health Technol Assess. 2000;4(38):1-130. Review.

16.

Combining randomized and non-randomized evidence in clinical research: a review of methods and applications.

Verde PE, Ohmann C.

Res Synth Methods. 2015 Mar;6(1):45-62. doi: 10.1002/jrsm.1122. Epub 2014 Jun 3. Review.

PMID:
26035469
17.

Review of guidelines for good practice in decision-analytic modelling in health technology assessment.

Philips Z, Ginnelly L, Sculpher M, Claxton K, Golder S, Riemsma R, Woolacoot N, Glanville J.

Health Technol Assess. 2004 Sep;8(36):iii-iv, ix-xi, 1-158. Review.

18.

Bayesian evidence synthesis for exploring generalizability of treatment effects: a case study of combining randomized and non-randomized results in diabetes.

Verde PE, Ohmann C, Morbach S, Icks A.

Stat Med. 2016 May 10;35(10):1654-75. doi: 10.1002/sim.6809. Epub 2015 Nov 22.

PMID:
26593632
19.

[Meta-analysis of the Italian studies on short-term effects of air pollution].

Biggeri A, Bellini P, Terracini B; Italian MISA Group.

Epidemiol Prev. 2001 Mar-Apr;25(2 Suppl):1-71. Italian.

PMID:
11515188

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