Biostatistical Methods II: Logistic Regression and Survival Analysis

The most common types of analysis in the healthcare or pharmaceutical industries are logistic regression models and survival analysis. To analyze data with dichotomous outcomes, such as having (or not having) a certain disease, one often needs to use a logistic regression model. Survival analysis focuses on time to event data. The event of interest can be death (most commonly encountered) or occurrence of a disease.

In this course, students learn to identify situations when it is best to utilize logistic regression and survival analysis and how to run these types of analysis by using SAS software. Sample size calculation and power analysis are also introduced.

Topics include:

• Simple logistic regression
• Multiple logistic regression
• Goodness of fit and model diagnostics for logistic regression
• Introduction to survival analysis
• Cox Proportional Hazards Model
• Model diagnostics for Cox Proportional Hazards Model
• Nonproportional Hazards Model
• Power and sample size analyses

Practical experience:

• Use SAS to run logistic regression and survival analysis
• Write method and result sections for a scientific paper

Software: Students must download and install SAS OnDemand for Academics: Enterprise Guide. There is no additional cost for this product. Registration and download information will be provided by the instructor on the start date.

Course typically offered: Online in Winter and Summer

Prerequisites: Completion of Biostatistical Methods I: Linear Regression and ANOVA required.

More Information: For more information about this course, please contact appliedscience@ucsd.edu.

Note: Instructions for ordering the course reader (e-textbook) will be provided on the first day of class.

Course Number: BIOL-40316
Credit: 3.00 unit(s)
Related Certificate Programs: Biostatistics

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7/9/2024 - 9/13/2024

$725

Online

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• SECTION ID:

  178511

• CLASS TYPE:

  Online Asynchronous.
  
  This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
  You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

• INSTRUCTOR:

  Li, Arthur, Biostatistician, City of Hope; Instructor, Department of Preventative Medicine, USC

  Arthur Li holds an M.S. in Biostatistics from the University of Southern California. Currently, he is a biostatistician at the City of Hope National Medical Center. Li developed and taught an introductory SAS course at USC for the past six years, and teaches a clinical biostatistics sourse at UC San Diego Extension. In addition to teaching and working on cancer-related research, Li wrote a book titled “Handbook of SAS® DATA Step Programming” which was released in April 2013.  

• TEXTBOOKS:

  No textbook required.

• POLICIES:

  No refunds after: 7/8/2024.
  

• NOTE:

• DATE & LOCATION:

  7/9/2024 - 9/13/2024
  extensioncanvas.ucsd.edu
  You will have access to your course materials on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.