It means if we are building our model in which we have selected four independent variables and one dependent variable, and if we choose the enter method, it means all the independent variables will be given equal importance in our model. Now enter method is very popular and the recommended method for multiple regression analysis because it's a kind of forced entry method. By default, the method that is selected for doing regression analysis is the enter method. We are going to understand all these methods one by one. If we click on the method, we will see five methods listed, which are enter method, stepwise method, remove method, backward and forward method. Now once we specify our model, we have to select the method for doing regression analysis. So we will put Current Salary as the Dependent variable and education, employment category, beginning salary and previous experience as the Independent variable. Suppose we are building our model in which we predict the Current Salary of employees based on the education level of the employees, their employment category, and their beginning salary. So, we are not supposed to take any non-metric dependent variable. For example, the employment category can be taken as a dependent variable, but in that case, we are specifying our model wrongly. We can also take a non-metric variable as a dependent variable. It means in the case of multiple regression, we can take only one dependent variable, and we are supposed to take it as a metric variable. We can see a Dependent variable and Independent variable box and a Block. This is the same dialog box that we used earlier. In regression, we locate the Linear regression as follows:Īfter clicking on Linear Regression, we will see a dialog box like this: If we want to perform a Multiple Regression analysis, we will go to our Analyze menu, and then find out the Regression. In this section, we will learn about the method of Regression. This requires using syntax.Next → ← prev Enter method of Multiple Regression It is also possible to use the older MANOVA procedure to obtain a multivariate linear regression analysis. The string in quotes is an optional label for the output. LMATRIX 'Multivariate test of entire model' The syntax to get the complete analysis at once, including the omnibus test for all predictors and dependents, would be: Suppose you have predictors X1, X2, and X3, and dependents Y1 and Y2. To do that, you would have to use syntax. In some cases people want a multivariate test for the entire regression. Checking the box for Parameter estimates in the Options dialog box produces the regression coefficients for each predictor for each dependent. The output from this will include multivariate tests for each predictor, omnibus univariate tests, R^2, and Adjusted R^2 values for each dependent variable, as well as individual univariate tests for each predictor for each dependent. To print the regression coefficients, you would click on the Options button, check the box for Parameter estimates, click Continue, then OK. Place the dependent variables in the Dependent Variables box and the predictors in the Covariate(s) box. The simplest way in the graphical interface is to click on Analyze->General Linear Model->Multivariate. You will need to have the SPSS Advanced Models module in order to run a linear regression with multiple dependent variables.