Overview of Using Observational Data in Comparative Effectiveness Research (CER)
- When to use observational studies in CER
- Observational study biases
- Observational study data sources
Cancer Registries and Data Linkage
- Data linkage definition
- Why cancer registries link their data
- Basics of data linkage methods
SEER-Medicare and Other Data Sources
- Uses of cancer registry data
Overview of Analytic Methods I
- Correlation definition
- Statistical methods for continuous outcome variables
- Simple linear regression and multiple linear regression
Overview of Analytic Methods II
- Statistical methods for categorical data
- Mantel Haenszel Method
- Logistic regression
Longitudinal Data Analysis
- Longitudinal data situations and the problems of repeated measures
- Common approaches to measure change over time
- Understanding basic results obtained from longitudinal analysis of linear and logistic regression
Advanced Methods in CER I
- Limitations of randomized clinical trials and advantages of observational studies
- Propensity score definition and estimation
- Checking the proper use of propensity scores
Advanced Methods in CER II
- Endogeneity bias definition
- Conditions and properties of instrumental variable estimation and models
Survival Analysis
- Censoring and person-time
- Application of life tables
- Kaplan Meier estimator
- Using the log-rank test to compare survival curves
- Hazard function definition and hazard ratio computation
- Applying the Cox proportional hazards model
Analysis of Medical Cost Data in Observational Studies
- Importance of medical cost analysis
- Basic elements of medical cost data
- Types of medical cost studies and their analytical methods
Healthcare Policy Research
- Objectives and stages of the policy-making process
- Comparison and contrast of CER and policy research
- Policy changes and evaluation results of a case study