Then a new dialog box will appear with the name of Linear Regression, and then enter the variable competence and motivation to box Independent (s), and then enter the Dependent box to the performance variable, then click the Statisticsĥ. Next, from the SPSS menu select Analyze- Regression- LinearĤ. The next step, click the Data View and enter research data in accordance with the variable Competency, Motivation, Performance.ģ. Turn on the SPSS program and select the Variable View, furthermore, in the Name write Competency, Motivation, Performance. Step By Step to Test Multicollinearity Using SPSSġ. For the manager of the collected data competence, motivation and performance of employees from 40 samples. Research title is "Influence of Competence and Motivation on Employee Performance". If the VIF 10, then there is multicollinearity.Ī company manager wants to know whether the regression models multicollinearity symptoms or not.If the VIF value lies between 1-10, then there is no multicollinearity.Test muticollinearity as a basis the VIF value of multicollinearity test results using SPSS. Good regression model should not happen correlation between the independent variables or not happen multicollinearity. In addition, multicollinearity test done to avoid habits in the decision making process regarding the partial effect of independent variables on the dependent variable. Similarities between the independent variables will result in a very strong correlation. Multicollinearity Test Example Using SPSS | After the normality of the data in the regression model are met, the next step to determine whether there is similarity between the independent variables in a model it is necessary to multicollinearity test.
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