Binary Logistic Regression

This example applies to the Healthcare Module. For more information, go to www.minitab.com/healthcare-module.

Example

In this worksheet, Left without Being Seen is the response. The response event is Yes. Wait Time is a continuous predictor, and Reason is a categorical predictor.

C1-T	C2	C3-T
`Left without Being Seen`	`Wait Time`	`Reason`
No	13	Feeling better
Yes	58	Excessive wait time
No	9	Feeling better
No	11	Other commitments

How-to

From the Healthcare KPIs: Predict Leaving without Being Seen dialog box, select Binary Logistic Regression, then click OK.
From the drop-down list, select Response in binary response/frequency format.
In Response, enter the column that contains the binary variable indicating whether a patient left without being seen. Binary variables are categorical variables that have two possible levels, such as pass/fail or true/false. The response is also called the Y variable.
In Response event, select the value that represents a patient left without being seen.
(Optional) In Frequency, enter the column that contains the counts that correspond to the response and predictor values.
In Continuous predictors, enter the continuous variables that may explain or predict whether a patient leaves without being seen. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments, such as facility, that may explain or predict whether a patient leaves without being seen. The predictors are also called X variables.
Click OK.

Tip

For more information about this analysis, click Help in the main dialog box.