In the previous two lessons, we focused on regression analyses using Scale predictors. 3.5 Regression with the interaction of two categorical predictors.3.4 Regression with two categorical predictors (main effects model).3.3 Regression with a 1/2/3 (multicategory) variable.3.1 Regression with a 0/1 (dummy) variable.We are not making any presumptions about the relative importance of the variable. So, Enter method is typically used in case of theory testing, and all the variables are given equal importance. While in the Variable Removed box, we cannot see any other variable. Our dependent variable is the current salary. In the Variables Entered box, we have all our independent variables. The first table is the Variable Entered or Removed in the model. So, if we select the enter method and keep all the options at their default and press Ok, we will get the following output: So if we are building a theory in which we have to select an appropriate regression method, I recommended you to go for the Enter method. Regression is a great tool for building theories in which we have to predict certain variables based on certain other variables. The model is not making any presumption that one of these variables is more important as compared to other variables that typically happen in the case of theory building. 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. Next → ← prev Enter method of Multiple Regression
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