Advanced Statistical Modeling in Healthcare Epidemiology
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Description
This exam evaluates knowledge of advanced statistical modeling techniques in healthcare epidemiology, focusing on multivariable and survival analysis essential for health research.
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Exam Details
Duration: 60 minutes
Prerequisites: Quantitative Methods In Epidemiology, Intermediate Biostatistics
Key Topics
- Multivariable Modeling
- Survival Analysis
- Longitudinal Data Analysis
- Model Selection
Learning Outcomes
- Demonstrate Knowledge Of Advanced Models
- Discuss Model Assumptions
- Explain Model Selection Criteria
Full Description
This exam focuses on advanced statistical modeling techniques relevant for epidemiological research. Core areas include multivariable modeling, survival analysis, and longitudinal data analysis.
These modeling capabilities are vital for understanding complex health outcomes and informing clinical decision-making. Mastery of these techniques leads to improved design and interpretation of epidemiological studies.
Candidates will be tested on their ability to explain the assumptions underlying various statistical models and how to select the appropriate model based on study objectives.
Discussion may involve real-world applications and examples of how advanced statistical models improve patient care outcomes.
Sample Questions
- What assumptions must be met for a multivariable model to be valid?
- How does survival analysis differ from traditional statistical methods?
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