Stats #04: Using SPSS to Develop a Logistic Regression Model
Content: This three hour training class will give you a general introduction in how to use SPSS software to compute logistic regression models. Logistic regression models provide a good way to examine how various factors influence a binary outcome. There are three steps in a typical logistic regression analysis: First, fit a crude model. Second, fit an adjusted model. Third, examine the predicted probabilities. These steps may not be appropriate for every logistic regression analysis, but they do serve as a general guideline. In this presentation, you will see these steps applied to data from a breast feeding study, using SPSS software.
Objectives: In this class, you will learn how to:
- compute and interpret simple odds ratios;
- relate the output of a logistic regression model to these odds ratios; and
- examine the assumptions behind your logistic model.
Teaching strategies: Didactic lectures and individual computer exercises.
IRB Education Credits: This class does not qualify for IRB Education Credits (IRBECs).
Notes: There are no statistical prerequisites for this class. No statistical experience is necessary. This class will provide hands-on computer experience in the CMH computer lab using SPSS software. You will use two SPSS data sets for practice exercises: bf.sav and titanic.sav.
Outline:
- Seating in the computer lab
- Overview of the STATS web pages
- Consulting services that I provide
- Installing SPSS terminal server (draft)
- Description of the breast feeding data set
- Titanic mortality data set
- Definition: Categorical data
- Definition: Continuous data
- Inputting a two-by-two table into SPSS
- Definition: Odds
- Odds ratio versus relative risk
- The concepts behind the logistic regression model
- Overfitting the data
- Guidelines for logistic regression models
- SPSS dialog boxes for logistic regression
- Please fill out an evaluation form