Analysis of Observational Health Care Data Using SAS
Publisher: SAS Press
An anthology of techniques for health care studies based on records and surveys of patient outcomes, including insurance databases, with references to SAS techniques for data handling and analysis. Contains real-world examples.
Editions
Paperback (2010)
Paperback
Year: 2010
ISBN: 978-1-60764-227-5
Pages: 448
Publisher’s list price: 64.95
Contents
- 1. Introduction to Observational Studies
- 2. Propensity Score Stratification and Regression
- 3. Propensity Score Matching for Estimated Treatment Effects
- 4. Doubly Robust Estimation of Treatment Effects
- 5. Propensity Scoring with Missing Values
- 6. Instrumental Variable Method for Addressing Selection Bias
- 7. Local Control Approach Using JMP
- 8. A Two-Stage Longitudinal Propensity Adjustment for Analysis of Observational Data
- 9. Analysis of Longitudinal Observational Data Using Marginal Structural Models
- 10. Structural Nested Models
- 11. Regression Models on Longitudinal Propensity Scores
- 12. Good Research Practices for the Conduct of Observational Database Studies
- 13. Dose-Response Safety Analyses Using Large Health Care Databases
- 14. Costs and Cost-Effectiveness Analysis Using Propensity Score Bin Bootstrapping
- 15. Incremental Net Benefit
- 16. Cost and Cost-Effectiveness Analysis with Censored Data
- 17. Addressing Measurement and Sponsor Biases in Observational Research
- 18. Sample Size Calculation for Observation Studies
- Index
