The Nominal Logistic Regression is used to perform logistic regression for nominal response variable with one or more predictors. Ordinal variables are variables with 3 or more levels and these levels have no natural ordering.
1. Choose ProcessMA > Statistics > Regression > Nominal Logistic Regression.
2. In Response, select the column containing the response values.
3. In Reference event, choose the reference event of the response variable.
4. In Frequency (Optional), select the column containing frequency data.
5. In Model, select the columns containing variables to be included in the model.
6. In Factors (Optional), select the columns containing variables in the model that are factors.
7. Click OK.
Note To select a column of data into a textbox, double-click on any of the column names shown in the list on the left of the dialog box while in the textbox.
Response: Numeric.
Frequency: Integer; Must be greater than zero; Must have the same number of data points as the variable.
Model: Text or Numeric; Must have the same number of data points as the variable.
Factors: Text or Numeric; Must have the same number of data points as the variable.
You want to understand the type of sports people like to play and how is this associated with their gender and age.
1. Open worksheet ProcessMA > Tools > Data Files > Regression.xls.
2. Choose ProcessMA > Statistics > Regression > Nominal Logistic Regression.
3. In Response, select P – Sports.
4. In Model, select Q – Gender, R – Age.
5. In Factors (Optional), choose Q – Gender.
6. Click OK.
Interpretation
From the logistic regression table, you can obtain the coefficients for the regression model. There are two sets of parameter estimates, Squash and Tennis as compared to Golf.