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The robustness of analyses has been assured through a rigorous approach using both population weightings and sensitivity analysis.
With follow-up periods between 17 and 25 years, a sufficient number of deaths can be expected to warrant sufficient robustness of analyses.
Thus, inferring events based on non-systematically selected event costs is likely to provide only a piece of a complex picture, and our tools motivate further investigation into the robustness of analyses based on DTL reconciliation.
Secondly, although the nature and extent of the significant treatment results support the robustness of analyses, the pattern of changes during the year-long study could potentially have been more fully characterized by including more assessment points.
To increase the robustness of analyses, we assessed the temporal changes in each treatment by pooling data over successive generations (i.e. data for generations 1 4, 4 10 and 13 22); these pooled data were used to estimate the three successive matrices G1, G2 and G3, respectively.
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To test the robustness of our analyses, we performed three sensitivity analyses.
To check the robustness of our analyses, we calculated Bayesian random effects meta-analyses for all available direct comparisons and carried out several sensitivity analyses, including a restriction to trials in patients with musculoskeletal conditions (data shown in web extra appendix 2).
Univariate sensitivity analyses were performed to explore the robustness of the analyses [ 18].
To maximise the robustness of the analyses, the total pool of controls was the comparator for each diagnostic group, an approach adopted in other UKCCS analyses (e.g. Beral et al, 2001).
Table 2 Recommendations related to data quality and methodologies to improve the robustness of functional analyses based on global fisheries datasets.
In the second part of the paper, a new method to improve the computational robustness of SDA analyses is proposed.
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