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These variables were entered into multivariate logistic regression models conducted using the backward stepwise method: first, all the variables have been included, then, using a stepwise procedure, the variables with not statistically significant association have been removed.
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The variance associated with AN abundance in the PLS model conducted using the combined datasets from both bays was significantly related to salinity, POC and Tmax 7d (F3,167 = 111.88, p<0.0001).
All analyses involved multilevel modeling, conducted using HLM 6.08 (Raudenbush, Bryk, Cheong, & Congdon, 2000).
Data processing and descriptive analyses were conducted using Version 9.3 of the SAS System for Windows (Cary, NC, USA), with multilevel logistic modelling conducted using adaptive quadrature via the xtmelogit command of Stata Version 12 for Windows (College Station, TX: StataCorp LP).
To understand the mechanistic aspect between surface functionalities and the chromium ions, kinetic models were conducted using pseudo-second-order model and intraparticle diffusion model, respectively.
Model selection for the linear mixed-effects models was conducted using the Akaike information criterion.
Modeling was conducted using Modeller 9v11.
The regression of these models is conducted using limited data, and the meteorology parameter is not tested against the data from other climate regions.
All logistic regression models were conducted using the F4PNLWT sampling weight and the complex sampling design options (svy commands) within STATA 12.
Some possible models were conducted using stepwise procedures.
All models were conducted using PROC GENMOD in SAS version 9.2 (SAS Institute Inc., Cary, NC).
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