(untitled) (Journal of Academic Research, 2024)
This study aimed to show how a mediating variable affects the parameters of a simple linear regression model, basically clarifying the real influence of the independent variable on the dependent variable by adding the mediating variable as a new independent variable in the regression equation. Using a simple random sampling method, 100 companies from the industrial sector in Misurata were chosen. The data were analyzed using statistical methods and tested for the mediating variable according to the study (Baron & Kenny, 1986), along with path analysis via the AMOS program to identify both direct and indirect effects. The Sobel Test was applied to check the significance of the mediating variable’s indirect effect. After analyzing the study data and its hypotheses, several findings were made, the most important being the need to include the mediating variable in the regression equation. This leads to improved performance of the regression model, making it more accurate in depicting the relationships between the variables, providing better explanations, accounting for the variance in the dependent variable, and being more effective in clarifying the total direct and indirect effects of the independent variable on the dependent variable.