individual is positive for the outcome, and 0 when they are negative.

If you do not have an outcome column coded this way, use the data management commands in your

software to generate a new variable coded as 0 for those who do not have the outcome, and 1 for

those who have the outcome, as shown in Table 18-1.

2. Make sure your data set has a column for each predictor variable, and that these columns are

coded the way you want them to be entered them into the model.

The predictors can be quantitative, such as age or weight. They can also be categorical, like

gender or treatment group. You will need to make decisions about how to recode these variables to

enter them into the regression model. See Chapter 17, where we describe how to set up categorical

predictor variables.

3. Tell your software which variables are the predictors and which is the outcome.

Depending on the software, you may do this by typing the variable names, or by selecting the

variables from a menu or list.

4. Request the optional output from the software if available which may include:

A summary of information about the variables, goodness-of-fit measures, and a graph of the

fitted logistic curve

A table of regression coefficients, including odds ratios (ORs) and their 95 percent

confidence intervals (CIs)

Predicted probabilities of getting the outcome for each individual, and a classification table

of observed outcomes versus predicted outcomes

Measures of prediction accuracy, which include overall accuracy, sensitivity, and

specificity, as well as a Receiver Operator Characteristics (ROC) curve

5. Execute the model in the software.

Obtain the output you requested, and interpret the resulting model.

Interpreting the Output of Logistic Regression

Figure 18-4 shows two kinds of statistical software output from a logistic regression model produced

from the data in Table 18-1. The output presented is not from a particular command in a particular

software. Instead, typical output for the different items is presented to enable us to cover many

different potential scenarios.