Build a Breast Cancer Logistic Regression Model using SAS Studio

While regression models are used to predict the value of a target variable, logistic regression models, on the other hand, are used to predict the class or classification of the target variable. When the target variable has only two possible classes (yes or no), the model is referred to as the binary logistic regression model.

In this assignment, you will use SAS Studio to build a binary logistic regression model for a breast cancer data set Download breast cancer data set.

To prepare for this Critical Thinking Assignment:

Review the module's interactive lecture and its references.

Use the browser-based version of SAS Studios available via SAS OnDemand. Detailed instructions are provided in the document SAS OnDemand Instructions.

To complete this assignment:

Complete these steps:

Step 1:

Upload the "breast-cancer.csv" file to SAS Studio

Import the "breast-cancer.csv" file into the SAS Studio dataset format and name the resulting data set "breastcancer". Hint: Uncheck the OPTIONS: Generate SAS variable names.

Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the results you obtained. The screenshot should have the current date and time.

Step 2:

Build a binary logistic regression model as follows:

Response: VAR1 with Event of interest: recurrence-events

Classification variables: VAR2

Parameterization of Effects: Coding: Reference coding, MODEL: use default settings

Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the statistics test results you obtained. The screenshot should have the current date and time.

Step 3:

Summarize your work on this assignment as follows:

Interpret the statistics test results you obtained from your work. Interpretation of results should be relevant and accurate.