1. Stats Tutorial

2. Is My Coin Fair? Assume it is no different from others (null hypothesis) When will you no longer accept this assumption?

3. Beware Multiple Comparisons! If you give patients a placebo and test for 6 different things, what’s the chance that one thing will be found to be “statistically significant (p< 0.05)” by chance alone?

4. Answer.95x.95x.95x.95x.95x.95=0.74 74% chance that you won’t cross the magic 0.05 threshold OR 26% chance that you will conclude there’s a real difference when there isn’t

5. Confidence Intervals RR =1 no difference RR < 1 treatment helps RR > 1 treatment harms Treatment Event Rate Control Event Rate RREstimate 95% CI ¼ 2/40.50? 5/2010/200.5? 10/4020/400.5? 25/10050/1000.5? 250/1000500/10000.5?

6. Confidence Intervals RR =1 no difference RR < 1 treatment helps RR > 1 treatment harms Treatment Event Rate Control Event Rate RRActual 95% CI ¼ 2/40.500.07-3.5 5/2010/200.50.21-1.2 10/4020/400.50.26-0.9 25/10050/1000.50.34-0.74 250/1000500/10000.50.44-0.57

7. Sample Questions

8. Question In a sample of 100 neonates, the mean total WBC is 7500 cells/mm 3 with SD 1500 cells/mm 3. If total WBC is normally distributed, then approximately 50% of individuals will have a value  between 6000 and 9000  above 9000  below 6000 or above 9000  below 7500

9. Normal Distribution mean = 7500 68% 95%

10. Answer Below 7500 In a normal distribution, the mean and the median are the same. If the median is 7500, then half are above and below.  6000-9000 is +/- 1 SD, this encompasses 68% of the population  Above 9000 is > 1 SD and that’s (50% - 34%) = 16%  Below 6000 or above 9000 is 1 SD or 16% +16%=32%

11. Question Again, assuming a normal distribution of WBC, a randomly selected neonate would have a WBC > 10,500: a)  1% of the time b)  2.5% of the time c)  5% of the time d)  16% of the time

12. Answer 2.5% of the time You are 2 SD from the mean; 95% of the distribution lies within 2 SD of the mean. 5% of the distribution lies outside the 95% area. Half (2.5%) above and half (2.5%) below.

13. Question A case-control study compares treatment in insured and Medicaid patients with preterm labor. The 95% CI for the odds ratio for Medicaid patients being more likely to be under-treated than insured patients was 1.1 to 2.5. Which is true? a)95% of the time Medicaid patient are more likely than insured patients to be under-treated b)The results are not statistically significant (p> 0.05) c)The probability is 95% that odds ratios in similar studies would fall within these limits d)Since the observed odds ratio falls in the center of these limits, the probability is 95% that it is the correct value

14. Answer The probability is 95% that odds ratios in similar studies would fall within these limits  Two of the 3 are pure-nonsense distractors.  The 95% CI for the OR does not cross 1, so there is a statistically significant difference, p < 0.05.

15. Question An evaluation of prophylactic vancomycin to prevent line-associated sepsis enrolls 500 neonates. Subjects are randomly assigned to either vancomycin (n=250) or placebo (n=250). A 20% reduction in risk is considered clinically significant and  = 0.05.

16. Question Line-sepsis occurs in 65 of the placebo group and 50 in the vancomycin group. How many neonates would need to receive prophylactic vancomycin to prevent one from developing line-sepsis?

17. Answer NNT =17 SepsisNo Sepsis Vanco50200250 Placebo65185250 Totals115385500 EER = 50/250=.2 CER = 65/250=0.26 RR= 0.2/0.26= 0.77 ARR=0.26-0.20=0.06 NNT=1/0.06=17

18. Question The authors report RR = 0.77 (95% CI 0.5435 to 1.089) You conclude that:  There is a statistically significant decrease in line-sepsis in the vancomycin treated group  The proportion with line-sepsis is the same between groups  The study has proven that prophylactic vancomycin is not effective  A larger study is indicated

19. Answer A larger study is indicated  The 95% CI of the RR crosses 1 so there is not a statistically significant difference.  The 95% CI includes a clinically significant effect.

20. Question The results of 5 screening tests for identifying fetal anemia are presented below. TestSensitivitySpecificity Peak systolic velocity.69.89 SD ratio.56.94 Sinusoidal FHR.22.98 Serial growth.55.91 MSAFP.47.82

21. Question 1.The test, if negative, that best helps to rule OUT fetal anemia is: 2.The test, if positive, that best helps to rule IN fetal anemia is:

22. Answer 1.Peak systolic velocity It has the highest SENSITIVITY. SnOUT 2.Sinusoidal FHR It has the highest SPECIFICITY SpIN

23. Question A study evaluates the use of physical exam (PE) to identify PDA. The “gold standard” is echo. Eighty patients with PDA by echo were evaluated with PE as were 50 patients without PDA. The PE was positive in 56 of the neonates with PDA and in 10 of the neonates without PDA.

24. Question The sensitivity of PE for PDA in this study is a)10/50 = 20% b)24/80 = 30% c)56/80 = 70% d)40/50 = 80% e)56/66 = 85%

25. Question The prevalence of PDA in this study sample was  130/year  56/130 = 43%  80/130 = 62%  96/130 = 74%

26. Answer __________

27. Answer Sensitivity = PID  Disease = 80  Positive in disease = 56  Sensitivity = 56/80 or 70% Prevalence is disease in population at risk = 80/130 = 62% PDANo PDA PE + 561066 PE - 244064 8050130

28. Question PE is used in a patient that you estimate has a 50% chance of having PDA based on risk factors. What are the chances of having a PDA if the PE is positive?  35/100 or 35%  50/100 or 50%  35/50 or 70%  35/45 or 78%

29. Answer 35/45 = 78% PDANo PDA PE + 35(10)(45) PE - (15)40(55) 50 100 1.Assume 100 patients 2.Set desired prevalence (50%) 3.You already know that Sens = 0.7 and Spec = 0.8 4.Fill in TP=50 x 0.7 = 35 5.Fill in TN=50 x 0.8 = 40 6.Subtract to get the other 2 boxes 7.Calculate the PPV

30. Another Way Use Likelihood Ratio LR (+) = (A/A+C)/(B/B+D) LR (-) = (C/A+C)/(D/B+D) True (+) A False (+) B False (-) C True (-) D

31. Another Way Fagan Nomogram Plot pre-test probability estimate (prevalence, best guess) Draw line through the LR Read the post-test probability

32. Test Names to Know NominalOrdinalInterval or Ratio Difference in proportions Chi-square or Fisher’s exact (small frequencies) One or 2 meansStudent’s t-test Wilcoxon signed rank test (not normally distributed) More than 2 means ANOVA AssociationRelative RiskSpearman rhoPearson r Predict one variable from another Logistic regression Linear regression

33. Sample Question Because of my superior intellect, good study habits, and confident attitude, I will:  A. Approach this test with a smile on my face and a song in my heart.  B. Miss a few questions, but hey don’t we all?  C. Kick butt on this exam  D. All of the above