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As standard, one indicator factor loading was set to one, and correlations between the underlying latent factors were free to be estimated.
The subgroups of gender, age, social deprivation were explored for the primary direction, i.e. I to A to P and from I to P. As standard, one indicator factor loading was set to one, and initially correlations between the underlying latent factors were free to be estimated.
However, to date, there is no published research that has examined overall maternal exposures by identifying a total risk factor score for each indicator factor, and used LCCA to explore the synergistic effects of multiple risk factors and to screen high-risk groups in a high-risk birth defects area.
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Generally, Ellenberg's indicator factors indicated that the plots were sampled in cold climates and acidic soils with slightly more open and acidic habitats in the Alps than in the Scandes and slightly more continental and humid habitat in the Scandes than in the Alps (Figure S1).
While most neural-system-based climate expectation tests have been led by meteorologists or climate specialists, there is a lot of debate encompassing the estimation from the earlier information in deciding indicator factors (Saba and Rehman 2012).
Displaying the selected plots along the indicator values separately showed that the 403 Alps Scandes pairs were sampled in similar conditions for all six Ellenberg's indicator factors (Figure S2).
The plot values for each of the six Ellenberg's indicator factors as well as plot size were used to compute seven separate Euclidian distance matrices in each of the two regions.
To account for these imperfections in the pairing, we used the six Ellenberg's indicator factors and plot size or transformations of these variables as covariates in the subsequent models of β- and α-diversity.
Thus, contrary to our expectations, plot α-diversity was on average slightly higher in the Scandes than in the Alps even after directly accounting for slight differences in the six Ellenberg's indicator factors and plot size.
In addition, we carried out an OLS analysis of covariance (ANCOVA) to explore plot α-diversity in the two regions, with region as a main effect and the independent environmental variables (the six Ellenberg's indicator factors and plot size) as covariates.
Ellenberg et al. [44] ranked most of the plant taxa of Central Europe according to their occurrence optimum along key environmental gradients for plants (L, light; T, temperature; K, continentality; F, soil moisture; R, soil pH; N, soil fertility; henceforth termed Ellenberg's indicator factors) using an ordinal scale ranging from 1 (lowest) to 9 (highest) in terrestrial environments.
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