B4. In this exercise, run a stepwise multiple regression to predict depression scores, using the same predictors as in Exercise B3. In the first SPSS Linear Regression dialog box, enter cesd as the Dependent variable and the list of predictors in the Independent slot, as in the previous exercise. For Method, select “Stepwise.” For the Statistics options, you can omit Descriptives and Collinearity Diagnostics because you have already examined these, but this time you should select R squared change. Run the analysis and then answer the following questions:

(a) How many predictors were entered before the regression stopped?

(b) Which predictor variables made it into the regression—and which did not? Was the order of entry of predictors consistent with the values of the zero-order correlations?

(c) Looking at the Model Summary panel, what was the progression of the value of R2 from one step to the next—and were these changes significant? What happens to the standard error of the estimate with each progressive step?

(d) Were all models statistically significant—that is, was the value of R2 greater than zero at each step?

(e) Looking at the “Excluded Variables” panel—and focusing on Model 4, were any of the remaining predictors statistically significant?