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For baseline data, bias was 0.0 l/minute, limits of agreement ± 0.45 l/minute and percentage error ± 24.3%.
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Training data bias is not the only economic issue, however.
Seven quality elements that contain random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and baseline balance bias were assessed.
To minimise bias introduced by missing baseline data, multiple imputation was used.
Baseline data indicate that the possibility of bias was largely addressed through randomisation, with only a small difference noted between recruited groups.
Baseline data will be also examined to analyze systematic bias in attrition.
The use of baseline data that are strongly predictive of the key outcome measures considerably reduces but might not completely eliminate bias.
The characteristics of those for whom only baseline data were available ('baseline only group'; n=97) were compared with those of the '4 week group' (n=276) to check for participation bias.
No evidence of bias was found when baseline data were compared between groups recruited before and after revealing treatment allocation.
Baseline data were collected after randomisation, which might potentially have biased responses, but the data showed that groups were well matched.
Sixty-four percent of patients (N = 303) provided baseline NPS data, and those without baseline data were excluded from the respective analysis to limit missing data bias.
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