Your English writing platform
Discover LudwigSuggestions(1)
Exact(1)
For the remaining measures, formed as averages over each segment of trials, of times, counts and their ratios, a Gaussian error, identity link, and an unstructured correlation matrix were used.
Similar(57)
Participants primarily looked at room cues during the early segment of each trial, but primarily focused on the apparatus as the trial progressed, suggesting distinct, sequential stimulus functions.
As discussed earlier, to highlight any temporal differences in these measures over the course of the trial, data were extracted for the first 5 s (first segment) of the trial time and for the remaining 10 s (final segment).
Data were averaged for every 750-m segment of the trial.
Partial artifact rejection was performed by rejecting segments of the trials containing eye-blinks, muscle and SQUID artifacts.
For the estimated 80% of intervention participants who will not need an update of multifocal lens prescription (n = 234), the correction for the single-lens glasses will be matched with the prescription of the upper segment of their pre-trial multifocal glasses.
Similar to looking time measures, data was extracted for the onset and later segments of each trial.
Using segments of single trial data, rather than single time-points, makes the SNR less sensitive to the underlying source variation in power and phase, leading to a robust accurate measure even with a small number of single trials.
The critical segments of a trial included presentation of a sample stimulus in Task 1 (visual array or tone sequence), sample stimulus in Task 2, test stimulus and query display in Task 1 (requiring a same different response), and test stimulus and query display in Task 2 (requiring another same different response).
When uncertainty still persists in a substantial segment of the medical community, the trial has not achieved its primary goal, and the main aim of the trial remains unanswered.
We considered spontaneous activity data from three segments of the session comprising early, middle and late blocks of trials.
Write better and faster with AI suggestions while staying true to your unique style.
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