1. Statistical Fridays J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine

2. Session Review Sensitivity / specificity Predictive value Effect of disease prevalence The ROC curve

3. Session Overview Learn new concepts: Observations vary Observational vs. experimental data Graphing your data Example: 50 patients induced with TPL or PPF

4. Observations Vary Subject JH’s systolic BP is 151 mmHg. He applies 1 mL of 5% minoxidil to his scalp in a vain attempt to keep his remaining hair. 15 min later, his systolic BP is 148 mm Hg. Q: Did his BP decrease ? Q: May we state “BP decreased” ?

5. Observations Vary

6. When do things “differ”? Observations Vary

7. When do things differ? When statistical tests indicate so. Data nearly always “differ numerically” Only statistics tells us when numbers differ. There is no such thing as a difference that is not a statistical difference.

8. When do things differ? Only when they differ statistically.

9. Population v. Sample POPULATION : The theoretical cohort about which we wish to draw conclusions…………….. Examples: Patients with heart disease Pregnant women with hypertension Patients with antithrombin deficiency 1

10. SAMPLE: The specific subjects for whom we have measurements………………… Patients with heart disease 25 patients with classic angina Pregnant women with hypertension 45,420 pregnant women taking Atacand Patients with antithrombin deficiency The patient seen in clinic yesterday Population v. Sample

11. Population v. Sample: Models Statistical Model : –Device by which we infer properties about a population based on information obtained in a sample ALL MODELS ARE WRONG. Some are useful.

12. Statistical Model Example: Let x = TPL dose (mg/kg) at induction Let y = decrease in SPB at induction y =     x 

13. Types of Data Observational Experimental Retrospective Survey data Lack intervention Lack active randomization Prospective Active randomization Intervention Controls / blinding

14. Types of Data Observational Experimental ASSOCIATION CAUSATION Fifty (50) patients receive TPL or Propofol for induction. The  SPB for each is recorded. Fifty (50) patients are randomly assigned to receive either TPL or Propofol for induction. The  SBP for each is recorded.

15. Graphing Data Histograms Scatterplots Boxplots

16. Example: SBP data 100 measurements total: 25 SBP before TPL 25 SBP after TPL 25 SBP before PPF 25 SBP after PPF Calculate  SBP for each

17. HISTOGRAM

18. Histogram by Treatment

19. Scatterplot: before v. after

20. Scatterplot by treatment group

21. 0 1 2 3 4 5 6 7 8 910 12 14 16 18 20 PPF TPL Min Max Median Upper QuartileLower Quartile Boxplot of  SBP by treatment

22. Min Max Median Q1 Q3

23. Min Max Median Q1 Q3

24. Session Review New concepts: Observations vary Observational vs. experimental data Graphing your data Example: 50 patients induced with TPL or PPF Homework: 20 patients given spinals for C-section