CERTaIN: Observational Studies and Registries

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