Binary Logistic Regression

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

Example

In this worksheet, Bill Status is the response. The response event is Unpaid. Bill Amount is a continuous predictor, and Facility is a categorical predictor.

C1-T	C2	C3-T
`Bill Status`	`Bill Amount`	`Facility`
Paid	3006	Hillside Hospital
Paid	3750	Hillside Hospital
Unpaid	4060	Wellness General Hospital
Paid	3900	Wellness General Hospital

How-to

From the Healthcare KPIs: Predict Unpaid Medical Bills 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, bill status. 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 an unpaid bill.
(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 the bill will be unpaid. 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 the bill will be unpaid. The predictors are also called X variables.
Click OK.

Tip

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