TA17-1
Logistic regression uses a binary outcome variable. The goal is to model the probability of a “success” using one or more predictors.
Excel cannot do logistic regression.
The response variable for logistic regression must have modeling type “nominal” or “ordinal.” To assign the roles properly, right-click the column name of the response variable and select “Value Ordering.” The category that indicates a success should come first in this ordering. Click “Reverse” at the bottom right, if needed.
Use Analyze ➔ Fit Y by X.
For more than one predictor, use Analyze ➔ Fit Model.
Use Stat ➔ Regression ➔ Binary Logistic Regression ➔ Fit Binary Logistic Model.
Use Analyze ➔ Regression ➔ Binary Logistic.
TA17-2
Crunchit can only do logistic regression with one predictor. Use Statistics ➔ Regression ➔ Logistic.
TI calculators cannot do logistic regression.
Use the following commands to calculate and display a logistic regression. Note that additional predictors can be added in the model statement.
> model <- glm(Response ~ predictor, family=binomial)
> summary(model)