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Apart from synthesising and extending our previous results [2, 3], the main purpose of this paper is to present an unbiased experimental comparison between a large number of methods, controlling for the appropriate choice of hyperparameters and using a principled statistical methodology for the evaluation of the significance of the results.
Sophisticated statistical methods controlling for confounders and taking clustering of data into account were used.
Statistical methods controlling for confounders and taking into account clustering of data.
Area under the curve methods, controlling for baseline utility, will be used to calculate the number of QALYs accrued over the follow-up period.
Statistical methods controlling for confounders may not yet have been accepted practice in this field when some of these earlier papers were published, which may explain their limited use.
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Relationships among adherence, switch and relapse were examined using cohort and nested case control methods, controlled for age and sex.
Multiple testing was not corrected using the commonly used methods such as the method controlling for false discovery rate.
Meta-regression analysis (if feasible) will be conducted with restricted maximum likelihood (REML) estimation method, controlling for potential confounders (demographics, study methods, location, etc).
The relationship between depression, sleep, and physiologic correlates was assessed with multiple regression analyses using the backward selection method, controlling for age, duration of illness, and CP score.
The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis.
This method controls for codon usage, GC content, and the protein sequence.
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