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SC method is based on the graph theory and is insensitive to the structure of data.
FD is a technique that contributes to the structure of data collection process.
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First, we created an empiric semivariogram to examine the structure of data.
Due to the work of Tukey [ 10], Cleveland [ 11, 12], Cook and Swayne [ 13], and many others [ 14], it is now widely recognised that to fully appreciate the structure of data it must be examined visually.
PCA was performed using XLSTAT software (Addinsoft, Paris) to summarize and visualize the structure of data described by several quantitative variables, while obtaining the uncorrelated factors between them.
Nevertheless, choices about the structure of data sets to be analyzed can be quite different for a statistician versus a biologist.
Due to the structure of our data, we chose to use a mixed-effect modeling approach to account for the stochastic nature of the data collected at different sites across space and time.
Therefore, a mixed linear model seemed to be the most appropriate due to the structure of the data.
However, not all factors were tested for each model due to the structure of the data.
Note that during the MCMC algorithm, we allow the number of possible groups to vary and adapt to the structure of the data.
The calculation of inter-rater reliability as intra-class correlation coefficient [ 26, 27] showed sufficient consistency (r =.77); the widely used coefficient kappa was not applicable in our case due to the structure of the data matrix.
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