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An ANCOVA with a general linear model, with group and follow-up time point as fixed factors, was used to compare the average NRS scores at each follow-up period between the two groups.
Then we design a novel feature selection model with group sparsity, Deep Sparse SVM (DSSVM) that not only can assign a suitable weight to the feature dimensions like the other traditional feature selection models, but also directly exclude useless features from the feature pool.
For secondary outcomes we will use a mixed model with group as a fixed factor.
A mixed model with group as a fixed factor will be used for the other outcome measures.
To look for a difference in the mean statistics between groups, we used a linear model with group as the dependent variable.
Statistical analysis was conducted on log transformed AUC0-∞ and Cmax using an analysis of variance model with group as a fixed factor.
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We used a Bayesian, hierarchical, community occupancy model with group-specific hyper-parameters to estimate occupancy probabilities and species richness while accounting for imperfect detection.
Model-based (grouped) uses a flexible parametric model with grouped age and applying Eq. (2).
A two-level model with grouping of patients within centers would include residuals at the patient and center levels.
When analysing the D-probe phenotype, we used a five-group model with groups for MZ male, MZ female, DZ male, DZ female and DZ opposite-gender pairs.
By considering the new state-of-the-art techniques in this area, FDP modeling are classified and reviewed by the following groups: namely, modeling with pure single classifier, modeling with hybrid single classifier, modeling by ensemble techniques, dynamic FDP modeling, and modeling with group decision-making techniques.
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