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We can also bin trials on which detection was correct according to their response profile to further examine the distribution of trial performance.
Table 1 Distribution of trial types in Experiment 3 Constraints Absent trials 30% One-target trials 45% Two-target trials 25% Categorical targets 20% Specific targets 80% Resulting trial distribution Absent 30% One specific target 36% One categorical target 9% Two specific targets 16% Two categorical targets 1% One of each 8% Total 100%.
Importantly, subjects were not provided with any information regarding the distribution of trial types.
Figure 7f shows the distribution of trial time stamps.
We developed network diagrams to visualise the geometry of the available evidence; 21 22 that is, the frequency of comparisons between exercise and drug interventions to show the distribution of trial participants across different treatment modalities (and control).
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These constraints lead to the distribution of trials shown in Table 1.
The primary outcome measure for ASb, ASc, and ASl trials was the distribution of trials around SAS.
As can be seen in equation (2), the distribution of trials across comparisons affects the estimation of inconsistency variance.
Major reduction in values was obtained for RT distribution of trials immediately following an error in the 5th and 95th percentile.
When it was available, the distribution of trials was quite evenly spread across phase I trials (9.3%), phase II trials (13%), phase III trials (10.1%) and phase IV trials (8.7%).
The global distribution of trials by phase is shown in Table 2. ClinicalTrials.gov lists 25 phase 1, 49 phase 2, 30 phase 3, and 15 phase 4 AD trials.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com