Peter Cummings is Professor Emeritus, Department of Epidemiology, School of Public Health, University of Washington, Seattle WA. His research was primarily in the field of injuries. He used matched cohort methods to estimate how the use of seat belts and presence of airbags were related to death in a traffic crash. He is author or co-author of over 100 peer-reviewed articles.

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• Preface 1. Do Storks Bring Babies? 2. Risks and Rates 3. Rate Ratios and Differences 4. The Poisson Distribution 5. Criticism of Incidence Rates 6. Stratified Analysis: Standardized Rates 7. Stratified Analysis: Inverse-Variance and Mantel-Haenszel Methods 8. Collapsibility and Confounding 9. Poisson Regression for Rate Ratios 10. Poisson Regression for Rate Differences 11. Linear Regression 12. Model Fit 13. Adjusting Standard Errors and Confidence Intervals 14. Storks and Babies, Revisited 15. Flexible Treatment of Continuous Variables 16. Variation in Size of an Association 17. Negative Binomial Regression 18. Clustered Data 19. Longitudinal Data 20. Matched Data 21. Marginal Methods 22. Bayesian Methods 23. Exact Poisson Regression 24. Instrumental Variables 25. Hazards Bibliography Index

Peter Cummings is Professor Emeritus, Department of Epidemiology, School of Public Health, University of Washington, Seattle WA. His research was primarily in the field of injuries. He used matched cohort methods to estimate how the use of seat belts and presence of airbags were related to death in a traffic crash. He is author or co-author of over 100 peer-reviewed articles.

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• Preface 1. Do Storks Bring Babies? 2. Risks and Rates 3. Rate Ratios and Differences 4. The Poisson Distribution 5. Criticism of Incidence Rates 6. Stratified Analysis: Standardized Rates 7. Stratified Analysis: Inverse-Variance and Mantel-Haenszel Methods 8. Collapsibility and Confounding 9. Poisson Regression for Rate Ratios 10. Poisson Regression for Rate Differences 11. Linear Regression 12. Model Fit 13. Adjusting Standard Errors and Confidence Intervals 14. Storks and Babies, Revisited 15. Flexible Treatment of Continuous Variables 16. Variation in Size of an Association 17. Negative Binomial Regression 18. Clustered Data 19. Longitudinal Data 20. Matched Data 21. Marginal Methods 22. Bayesian Methods 23. Exact Poisson Regression 24. Instrumental Variables 25. Hazards Bibliography Index

Peter Cummings is Professor Emeritus, Department of Epidemiology, School of Public Health, University of Washington, Seattle WA. His research was primarily in the field of injuries. He used matched cohort methods to estimate how the use of seat belts and presence of airbags were related to death in a traffic crash. He is author or co-author of over 100 peer-reviewed articles.

Select Guide Rating

• Preface 1. Do Storks Bring Babies? 2. Risks and Rates 3. Rate Ratios and Differences 4. The Poisson Distribution 5. Criticism of Incidence Rates 6. Stratified Analysis: Standardized Rates 7. Stratified Analysis: Inverse-Variance and Mantel-Haenszel Methods 8. Collapsibility and Confounding 9. Poisson Regression for Rate Ratios 10. Poisson Regression for Rate Differences 11. Linear Regression 12. Model Fit 13. Adjusting Standard Errors and Confidence Intervals 14. Storks and Babies, Revisited 15. Flexible Treatment of Continuous Variables 16. Variation in Size of an Association 17. Negative Binomial Regression 18. Clustered Data 19. Longitudinal Data 20. Matched Data 21. Marginal Methods 22. Bayesian Methods 23. Exact Poisson Regression 24. Instrumental Variables 25. Hazards Bibliography Index