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The theoretical grouping of variables showed little change in predictive capability of OLS models.
In the first stage exploratory factor analysis (EFA) was used to provide the grouping of variables underline the complete set of item based upon the strong correlation.
In the first stage exploratory factor analysis (EFA) was used to provide the grouping of variables underline the complete set of item based upon the strong correlation [106, 110].
In order to reconfirm and cross check the results obtained from FA we also perform a Hierarchical Cluster Analysis (HCA) [40], which has similar concepts of grouping of variables with underlying common behavior.
The grouping of variables was carried out using standard thresholds.
The grouping of variables was carried out using conventional categories.
Similar(50)
In industrial data sets, groups of variables often move together.
Independent predictors of downloads included five groups of variables.
We discuss each group of variables in turn.
Tests for interaction were conducted between predefined groups of variables.
These common factors, for example, may be related to specific groups of variables, and it is interesting to analyze mechanisms of transmission to other groups of variables.
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