Advanced Topics in Healthcare Data Analysis
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About this course
In this course, you will learn about some of the complex data analysis tools and techniques that you will need to derive actionable insights from healthcare data, as well as continue learning R statistical programming to effectively apply these tools and techniques. Some of the topics covered in this course include causal inference, model specification, matching, fixed and random effects, repeated measures, dealing with missing data, and bootstrapping.
What you'll learn
- understanding of causal inference
- skills in model specification
- ability to apply matching techniques
- knowledge of fixed and random effects
- expertise in analyzing repeated measures
- strategies for dealing with missing data
- proficiency in bootstrapping
Skills you'll gain
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