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Multiple regression was used to identify the drivers best describing the variation in σpc data.
The study adopted a cross sectional design and Multiple Regression was used for data analysis.
Hierarchical multiple regression was used to predict parental stress and psychological distress.
Proposed mathematical model based on multiple regression was in complete agreement with experimental observation.
Multiple regression was used to undertake a simple form of time series analysis.
Multiple regression was used to test for associations between the built environment and metro station routes.
Multiple regression was then utilized to examine the factors affecting approaching speed.
Standard multiple regression was used to determine predictors of Stroop performance.
A multiple regression was performed to test the relation between the predictive performance of the model and the participants' accuracy for each of the 256 videos.
Multiple regression was more accurate than the RCI in determining a decline in performance relative to the baseline.
Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings.
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