MULTIPLE REGRESSION IN PRACTICE

Multiple Regression in Practice Student Names Affiliation Course Number: Course Name Instructor Name Due Date Why the Authors Used Multiple Regression Altenscheidt et al. (2024) investigated the contingent effect of sales managers’ aim and process control motive. The independent techniques used were multiple regressions embedded in a Structural Equation Modelling (SEM) framework. Predictors, such as main effects, two-way, and three-way interactions, were grouped and statistically analysed as blocks. The authors employed multiple regression because it permitted them to disaggregate the sales managers' unique and interactive impact of the control exerted over goal and process, and the impact felt by sales representatives on lead management effort, while holding other significant covariates constant. Given that a moderation and a three–way interaction hypothesis were being tested, multiple regression became a natural choice. Multiple regression analysis allows researchers to examine how numerous independent variables (predictors) jointly influence a dependent variable while accounting for the effects of other variables (Castro & Ferreira, 2023). Chi-square difference tests were used to assess the impact of additional interactions on roles assigned to the sales managers and the sales representatives. Appropriateness of Multiple Regression for the Study The choice of multiple regression was appropriate for the study by Altenscheidt et al. (2024). The study’s hypotheses concern how continuous predictors and their interactions influence a continuous outcome. Multiple regression naturally accommodates continuous moderators and interaction t...