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Another set of issues is the classification of trials design.
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If uncertainty remains over the classification of trial outcomes, studies should be scored as negative, unless the overall tone of the conclusion section favours the test drug.
Definitions used for classification of trial outcomes are inconsistent across studies and the terms 'sponsored by industry' and 'conflict of interest' have been applied in different ways.
In a majority of the studies on publication bias, methods for classification of trial outcomes are only reported to a very limited extent, though there are positive exceptions [ 5, 7].
The reviewers additionally state that our classification of individual trials as response or failure depends on an 'arbitrary' threshold.
The paper presents a novel pattern recognition approach for the classification of single-trial movement-related cortical potentials (MRCPs) generated by variations of force-related parameters during voluntary tasks.
These components enable classification of the included trials into trials with 'low risk of bias' or with 'high risk of bias'.
Median EQ-5D health utility scores were 0.68 (0.73, 0.73) and 0.60 (0.66, 0.66) at baseline based on Equation 1 and 2. Median EQ-5D health utility scores for each of the a priori determined SAQAF classifications at end-of-trial are reported in Table 2.
We agree with the authors that the classification of single EEG trials improves when ERD and ERS patterns are combined for multiple tasks.
No classification of the interventions of trials was provided in ChiCTR, so we only analyzed the publication rates for different interventions in clinicaltrials.gov.gov
To measure how much information is present in the pattern of neuronal activity on a single trial, we also computed the classification rate, the percentage of trials where the stimulus is correctly decoded from the neuronal responses by applying the linear discriminant.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com