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However, the exact impact of a single parameter cannot be estimated as in most studies multiple parameters were significantly changed and no systematic approaches were applied.
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Many segmentation algorithms are designed to analyse samples individually (see, e.g., [ 3- 16] and references therein), while most studies involve multiple samples, multiple tracks, or both.
Most studies contained multiple estimated ORs. Models accounted for the correlation between multiple results within the studies analyzed.
Most studies employed multiple baseline across subject designs or between group designs and most employed cognitive-behavioral techniques (i.e., desensitisation, emotive imagery, cognitive self-instruction, and reinforcement procedures).
Despite the complexity of smoking behaviors (quitting, relapsing, maintaining, occasional smoking and so on), the concept of self-efficacy was mostly measured on single occasions over the course of most studies reviewed; multiple measurements of concepts were not utilized in the randomized controlled trials.
Most studies presented multiple maps as figures within the manuscript, representing the different variables under investigation.
Most studies measured multiple response variables.
Most studies spanned multiple years, which would account for differences in seasonality of pneumonia, but a few were conducted for one year or less.
Most studies combined multiple approaches.
In all, however, most studies use multiple approaches.
Most studies used multiple outcome measures and analysed the effects using disaggregated cost-consequence frameworks.
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