Bias

1. Bias 역학 및 임상시험학 4학기 김현주

2. Learning Objectives • Key & Example Selection bias: - Control selection bias, Self-selection bias, Loss to follow-up, Differential surveillance, Diagnosis or Referral • Key & Examples Observation bias: - Recall bias, Interviewer bias, Differential and nondifferential misclassification • How the magnitude and direction of bias can affect study results • Avoided or minimized selection and observation bias ways

3. Overview Brief

4. Introduction • Two ways of Measures of disease frequency: ① Absolute comparisons: risk or rate differences ② Relative comparisons: risk ratios, rate ratios, odds ratios • Validity: - Internal validity(내적 타당도) - External validity(외적 타당도) or Generalizability: 연구방법, study population, subject-matters knowledge (biological basis of association) 예) 미국의 중년층 남성에서 관상동맥질환의 위험요인은 유럽 중년층 남성에게 적용할 수 있지만 성별에 따른 차이 때문에 미국이나 유럽여성에게는 일반화하기는 어렵다

5. Introduction • Eliminated for considered internal validity

6. Overview of Bias

7. Direction of Bias • Away from null 편의(bias) 0 7 측정값 5 참값 • Toward null 편의(bias) 0 7 참값 3 측정값

10. Selection Bias

12. Control Selection Bias

13. OR=(ad/bc) =(100ⅹ150)/(150ⅹ100)=1.0 → Pap smear와 cervical cancer와 관련성은 없음 OR=(ad/bc) =(100ⅹ100)/(150ⅹ150)=0.44 → Pap smear가 cervical cancer 위험을 56%감소시킴(toward the null)

15. Self-selection Bias

17. Differential Surveillance, Diagnosis, or Referral

19. Selection Bias in a Cohort Study

21. Loss to Follow up

22. Loss to Follow up

23. Loss to Follow up

24. Loss to Follow up

25. Loss to Follow up

27. Observation Bias

29. Recall Bias

30. 75%축소보고 Upward by 40% 아이에게 영향을 줄 수 있는 사회적으로 민감한 노출에 대한 보고 (예:약물, 술 등) 75%축소보고 downward by 37% [(2.7-1.7)/2.7ⅹ100%]=37%

31. Recall Bias

32. Recall Bias

33. Recall Bias

34. Recall Bias

36. Interviewer Bias

37. Interviewer Bias

39. Misclassification

40. OR =ad/bc =(200ⅹ200)/(100ⅹ100) =4.0 Away from the null OR =ad/bc =(200ⅹ250)/(100ⅹ50) =10.0 Toward the null OR =ad/bc =(100ⅹ200)/(100ⅹ200) =1.0

41. OR =ad/bc =(200ⅹ200)/(100ⅹ100) =4.0 Toward the null OR =ad/bc =(100ⅹ250)/(50ⅹ100) =2.5 • misclassification이 심하다면 null을 넘는 결과로 bias될 수 있음 • nondifferential exposure misclassification은 true null association에 영향을 • 주지는 않는다. • misclassified exposure variable가 3개 이상의 범주가 있을 때, bias가 적게 발생

42. Misclassification

43. Misclassification

45. Summary

46. Happy Day Thank you!!