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Specific areas of interest relating to the methods used included the choice of outcome metric, methods of dealing with sparse events, heterogeneity, publication bias and use of individual patient data.
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However, there is a lack of standardized sampling and metric methods to measure the level of exposure to nanoparticles, and the information related to possible adverse health effects is scarce.
Analytical expressions for the relationship between variance, where it is controlled by short-range correlation, and sample size for common forms of the correlation coefficient are developed using an orthogonal (L1-metric) method of measuring distance.
Therefore, the use of metric methods using a threshold is rather straightforward.
We also showed that misspecification in the count-to-distance transfer function can harm the performance of metric methods, while our model can adapt to unknown distributions within a parametric family.
Because of the incorporation of the gap metric method, the number of operational regimes is minimised.
We simulated another ensemble of datasets to compare non-metric and metric methods when the parameters provided to the different algorithms are not the correct ones.
In the L-P metric method, the distance of any present solution from the ideal solution is minimized (Banke et al. 2008): L − P = ∑ j = 1 k γ j f j x * j − f j x p 1 p, Open image in new window (13).
Also, the L-P metric method which is one of the famous methods of MCDM is applied in this paper.
The flame photo metric method was used for estimation of Potassium (U.S. Salinity Lab. Staff 1954).
The Euclidean distance metric method, as implemented in DNASTAR v5.1.2.
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