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Meta-analyses in orphan diseases and small populations generally face particular problems including small numbers of studies, small study sizes, and heterogeneity of results.
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Guideline on clinical trials in small populations, July 2006
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How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
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Much ado about nothing: a comparison of the performance of meta-analytical methods with rare events
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S Kosolo · 2013
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Interleukin-2 receptor antagonists for pediatric liver transplant recipients: A systematic review and meta-analysis of controlled studies
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A generalized linear modelling framework for pairwise and network meta-analysis of randomized controlled trials
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J. J. Gagne, L. Thompson, K. O’Keefe, and A. S. Kesselheim · 2014
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A re-evaluation of random-effects meta-analysis
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Pediatric liver transplantation
M. Spada, S. Riva, G. Maggiore, D. Cintorino, and B. Gridelli · 2009
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Bayesian methods for the design and interpretation of clinical trials in very rare diseases
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No solution yet for combining two independent studies in the presence of heterogeneity
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Small studies are more heterogeneous than large ones: a meta-meta-analysis
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Statistical methods for meta-analyses including information from studies without any events—add nothing to nothing and succeed nevertheless
O. Kuß · 2015
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Hartung-Knapp-Sidik-Jonkman approach and its modification for random-effects meta-analysis with few studies
C. Röver, G. Knapp, and T. Friede · 2015
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Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis
R. M. Turner, D. Jackson, Y. Wei, S. G. Thompson, and P. T. Higgins · 2015
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Methods to estimate the between-study variance and its uncertainty in meta-analysis
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