Multiple regression analysis is frequently and increasingly being employed in both experimental and non-experimental research. However, when data include predictor variables that are correlated, either unavoidably or due to conscious design choices, some regression results can become difficult to interpret. The paper presents an actual study to provide a heuristic demonstration that structure coefficients may be helpful in these cases.
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