Discriminant Analysis Stepwise Method
Method. Select the statistic to be used for entering or removing new variables. Available alternatives are Wilks' lambda, unexplained variance, Mahalanobis distance, smallest F ratio, and Rao's V. With Rao's V, you can specify the minimum increase in V for a variable to enter.
- Wilks' lambda. A variable selection method for stepwise discriminant analysis that chooses variables for entry into the equation on the basis of how much they lower Wilks' lambda. At each step, the variable that minimizes the overall Wilks' lambda is entered.
- Unexplained variance. At each step, the variable that minimizes the sum of the unexplained variation between groups is entered.
- Mahalanobis distance. A measure of how much a case's values on the independent variables differ from the average of all cases. A large Mahalanobis distance identifies a case as having extreme values on one or more of the independent variables.
- Smallest F ratio. A method of variable selection in stepwise analysis based on maximizing an F ratio computed from the Mahalanobis distance between groups.
- Rao's V. A measure of the differences between group means. Also called the Lawley-Hotelling trace. At each step, the variable that maximizes the increase in Rao's V is entered. After selecting this option, enter the minimum value a variable must have to enter the analysis.
Criteria. Available alternatives are Use F value and Use probability of F. Enter values for entering and removing variables.
- Use F value. A variable is entered into the model if its F value is greater than the Entry value and is removed if the F value is less than the Removal value. Entry must be greater than Removal, and both values must be positive. To enter more variables into the model, lower the Entry value. To remove more variables from the model, increase the Removal value.
- Use probability of F. A variable is entered into the model if the significance level of its F value is less than the Entry value and is removed if the significance level is greater than the Removal value. Entry must be less than Removal, and both values must be positive. To enter more variables into the model, increase the Entry value. To remove more variables from the model, lower the Removal value.
Display. Summary of steps displays statistics for all variables after each step; F for pairwise distances displays a matrix of pairwise F ratios for each pair of groups.
Selecting Stepwise Method Options
This feature requires the Statistics Base option.
- From the menus choose:
- Select Use stepwise method and then click Method.