| 1. |
- Friede, Tim, et al.
(författare)
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Recent advances in methodology for clinical trials in small populations : the InSPiRe project
- 2018
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Ingår i: Orphanet Journal of Rare Diseases. - : Springer Science and Business Media LLC. - 1750-1172. ; 13
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Forskningsöversikt (refereegranskat)abstract
- Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.
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| 2. |
- Unkel, Steffen, et al.
(författare)
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Independent Component Analysis for Three-Way Data With an Application From Atmospheric Science
- 2011
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Ingår i: Journal of Agricultural Biological and Environmental Statistics. - : Springer Science and Business Media LLC. - 1085-7117 .- 1537-2693. ; 16:3, s. 319-338
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, a new approach to independent component analysis (ICA) for three-way data is considered. The rotational freedom of the three-mode component analysis (Tucker3) model is exploited to implement ICA in one mode of the data. The performance of the proposed approach is evaluated by means of numerical experiments. An illustration with real data from atmospheric science is presented, where the first mode is spatial location, the second is time and the third is a set of different meteorological variables representing geopotential heights at various vertical pressure levels. The results show that the three-mode decomposition finds spatial patterns of climate anomalies which can be interpreted in a meteorological sense and as such gives an insightful low-dimensional representation of the data.
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