Logistic Regression is a statistical method used to assess the likelihood of a disease or health condition as a function of a risk factor (and covariates). There are two kinds of logistic regression, simple and multiple. Both simple and multiple logistic regression, assess the association between independent variable(s) (Xi) — sometimes called exposure or predictor variables — and a dichotomous dependent variable (Y) — sometimes called the outcome or response variable.
Task 1: Describe Logistic Regression
Before setting up a logistic regression, you should understand the basic concepts and formulas used in Logistic Regression.
Task 2: Setting Up Logistic Regression of NHANES Data
SUDAAN, SAS Survey and Stata are statistical software packages that can be used to analyze complex survey data such as NHANES.
- Key Concepts about Logistic Regression of NHANES Data Using SUDAAN and SAS Survey Procedures
- How to Use SUDAAN Code to Perform Logistic Regression
- How to Use SAS 9.2 Survey Code to Perform Logistic Regression
- How to Use Stata Code to Perform Logistic Regression
- Download Sample Code and Dataset
Task 3: Explain Differences Between SUDAAN and SAS Survey Procedures Logistic Regression Output
Reviewing the output from the SAS Survey Procedures and SUDAAN programs, you may have noticed slight differences caused by missing data in paired PSUs or how the programs handle degrees of freedom.