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In this study, a multiple regression approach for assessing land use impact on groundwater quality and quantity was developed by using the ANCOVA test to select regression model variables from key input variables to a widely used and well-calibrated SWAT (Soil and Water Assessment Tool) model system.
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We used a multiple regression approach, controlling for phylogenetic effects [20], [49], to analyze the influence of ecology, behavior, and sexually selected traits.
Therefore, we used a multiple regression approach which tests for the independent effect of each fatty acid class, controlling for correlations between fatty acid content and body weight.
We used a multiple regression approach to account for these interactions.
For dichotomous outcome variables, we used logistic regression, and the linear multiple regression approach was used for continuous outcome variables.
Finally, we propose a multiple regression approach to adjusting urinary analytes for differences in creatinine concentration.
For both models, a multiple regression approach was taken to predict Hm from age, Site Index, environmental data and RapidEye spectra and indices.
Factor scores were calculated by multiple regression approach, and each individual received a factor score for each dietary pattern.
The authors attempted to control for this alternative interpretation with a multiple regression approach.
Archetype maps were approximated using multiple regression approach.
These methods used either a multiple regression approach with different bones measurements or a simple regression logistic [28].
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