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Missing values (at least one item missing) were reduced from 15.3%to8.9%9% for the SCL indicator, from 4.9%to1.6%6% for the SWB indicator, and from 12.3% to 2.6% for the alcohol consumption indicator.
Missing values at 4th hour (n = 3 values) for ICP and CCP were treated by imputation.
We handled missing values at day 3 (n = 166, 22.1%) by taking the value one day before or after.
Among the teachers who responded to the TEDDICS and CSE scales, low proportions of missing values at the item level occurred (less than 1%%).
The second algorithm calculates matching and missing values at each level of the two trees and combines them at every level recursively which preserves the structural information between the two trees.
This subsection describes a generalized level-wise weighted tree similarity algorithm (GLW-wT-similarity algorithm) which combines matching and missing values at each level of two trees to preserve the structural information.
However, missing values at the internal part were treated by comparing this method for minimum error with other exact estimation methods discussed in "Linear interpolation", "Linear spline interpolation" and "Lagrange polynomial interpolation" sections.
The second generalized algorithm calculates matching and missing values at each level of the two trees and combines them at every level recursively, preserving the structural information present in the trees while calculating similarity.
The intention-to-treat analysis included last observation carried forward (LOCF) for missing values at end of treatment.
Missing values at evaluation visits were substituted with basal values.
Missing values at the health center level were observed.
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