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.
- 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
- 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 email@example.com.
- 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)
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