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For a transition towards sustainability, a well-orchestrated cross-sectoral multilevel approach is required.
The major motivation for a multilevel approach is that certain variations in an image, such as those due to edges are local in nature, and hence will be better captured by use of local (rather than global) information.
An additional advantage of this double comparative multilevel approach is that the variation of (unmeasured) factors, unique to each destination or origin country, are captured by the random intercept at the origin and destination levels and thus does not cause much bias in the parameters of the measured variables.
This multidisciplinary and multilevel approach is underlined by all included studies.
A multilevel approach is used in the analyses to correct for the fact that we randomized at the GP practice and not at the patient level.
Indeed, a multilevel approach is needed for implementing population based health behaviour interventions that can enhance the health and well-being of individuals [ 25].
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To take the hierarchical structure into account, a multilevel approach was used.
Possible improvements of the neural network model using a multilevel approach are discussed.
A multilevel approach was chosen for this research, drawing on representative data from four of the countries which participated in ICILS 2013, namely Australia, Germany, Norway and the Czech Republic.
A baseline model indicated that a multilevel approach was a better fit over a single level model (p ≤ 0.001) and that 11.9% of the variation in health service use was due to variation between prisons (not shown).
A multilevel approach was implemented in Saccharomyces cerevisiae to optimize the precursor module of the aromatic amino acid biosynthesis pathway, which is a rich resource for synthesizing a great variety of chemicals ranging from polymer precursor, to nutraceuticals and pain-relief drugs.
More suggestions(15)
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