Statistical Models: The Rest of the Story

1. Statistical Models: The Rest of the Story Scott L. Zeger Hurley-Dorrier Professor and Chair Department of Biostatistics The Johns Hopkins University Bloomberg School

2. What is a model?

3. What is a statistical model? Tool for those empirical sciences where signals come embedded in noise Lens through which to view data to better understand the signal Tool for quantifying the evidence in data about a particular truth we seek

4. Empirical science: search for “truth” Probability – statistical model Observed Value for a Representative Sample Truth for Population Statistical inference

5. You can not choose the best model because there isn’t one You can choose a useful model based upon prior scientific knowledge You can explore and report how your scientific findings vary over a set of other useful models You can average your results across useful models How to Choose the Best Model • Miminize the mean squared error • Minimize the Akaike Information Criterion (AIC) • Minimize the Bayesian Information Criterion (BIC) • Maximize the likelihood function • Cross-validate • Jackknife • Bootstrap • Boost, then bag • etc

7. Dollars Smoking Disease Death Causal Model

8. Iraq invasion Violence Death Causal Model

9. What Do We Know about Smoking and Medical Expenditures • WHO, U.S. Surgeon General and IARC say smoking causes 13 major diseases: • Lung cancer; COPD; atherosclerosis; MI; stroke; …. • In the U.S., most people receive treatment for major chronic diseases (e.g. lung cancer) • It cost money to treat your disease

10. What we know LITTLE about • Whether smoking causes people to use more or less medical services to treat smoking caused diseases • Whether smoking causes people without a major disease to seek more or less medical services • “I hate my doctor, she tries to take my cigs away” • “I go as often as I can afford; got to watch out for those diseases that can kill me”

11. Smoking Disease Dollars Smoking Dollars Competing Causal Models

12. Odds Ratios of Lung Cancer/COPD by Pack-years for Current and Former Smokers

13. Medical Expenditures for Persons with vs without Lung Cancer/COPD

14. Difference in Average Expenditures by Propensity to Have Disease

15. Smoking Attributable Burden for Cohort of 60 Million Who Started Under 21 Years Old, 1954-2000

17. “Know this”: $1 Trillion +- 0.2 T for 10% of pop Smoking Disease Dollars ??? Estimate well what you can; estimate poorly what you must. Don’t dilute decent causal estimates with causal speculates (unless you intend to make everything uncertain)

18. Iraq invasion Violence Death Causal Model

19. What We Know Well • 2,237 U.S. soldiers (DoD) • 99 British soldiers (British Govt) What We Know Less Well • 4,027 Iraqi police (News reports compiled by iCasualties.org) • 28,198 - 31,800 Iraqi civilians (IBC web-site) • The count includes civilian deaths caused by coalition military action and by military or paramilitary responses to the coalition presence (e.g. insurgent and terrorist attacks). It also includes excess civilian deaths caused by criminal action resulting from the breakdown in law and order which followed the coalition invasion. Compiled from eye-witness reports and news articles

20. Iraq invasion Violence Death ~30,000 Iraqi deaths Lack of sanitation Lack of clean water Poor nutrition Limited access to medical care Extreme stress and grief

23. 98,000 (95% CI: 8,000 - 194,000) without Falluja ~ 20 - 50% violent

24. Summary • A model defines the boundaries of an analysis and can determine what will be learned from data • Like a lens determines what you will see • Same model for two problems • Separate what can be estimated precisely from what can not • Prior knowledge about pathway • Too much uncertainty invalidates, whether it should or not

25. Timing of Proceeds Relative to Smoking Attributable Expenditures for Major Diseases Only

26. Smoking Attributable Fraction of Disease (SAF) and Dollars (SAFE)