1. مقدمه ‌ اي بر خطا

2. براي خطاي منظم و انواع سوگرايي تعريف ‌ هاي مناسب ارايه دهد. خطاي تصادفي، ‌ خطاي منظم، سوگرايي و مطالعه معتبر را با يكديگر مقايسه كند. رويكرد كمي به خطاي منظم ( سوگرايي ) را بپذيرد. مفهوم اعتبار يا روايی مطالعه را شرح دهيد.

3. ExplanationAssessment strategy Random variability95% CI, P-value ConfoundingAdjustment BiasThinking … Causal Eliminate alternative explanation, apply criteria for casual inference

4. PETER L. HAVENS, M.S., M.D. Associate Professor of Pediatrics and Epidemiology, Medical College of Wisconsin; Director, Pediatric HIV Program, Children's Hospital of Wisconsin, Milwaukee, Wisconsin STEPHEN B. HOLLY

5. MSE = Variance + Bias 2 SQUARE ROOT OF MSE ~ACCURACY (SQUARE ROOT OF) Bias (SQUARE) ~VALIDITY ~PRECISION SQUARE ROOT OF Variance Cochran

7. BIAS: threats to validity and interpretation Bias is the result of systematic error in the design or conduct of a study; a tendency toward erroneous results Systematic error results from flaws in either the (1) method of selection of study participants, or (2) in the procedures for gathering relevant exposure and/or disease information* Hence - the observed study results will tend to be different from the true results * systematic error is different from error due to random variability (sampling error)

8. If the design and procedure of a study are unbiased, the study is considered to be valid because its results will (on average) be correct.

9. سوگرايي انتخاب سوگرايي انتخاب وعلت رخداد آن را شرح دهد. سوگرايی انتخاب جبران شده را درک نمايد. نحوه ی مقابله با سوگرايي انتخاب را بداند.

10. عواملي كه باعث وقوع بيماري شده + عواملي كه منجر به حضور افراد در اين مطالعه خاص شده ‌ اند

11. Diseased Exposed + - +-+- REFERENCE POPULATION STUDY SAMPLE دو مثال

12. Selection bias Selection Bias: is present when individuals have different probabilities of being included in the study according to relevant study characteristics: namely the exposure and the outcome of interest Selection bias anytime there is systematic error in the selection of study subjects – cases or controls in a case-control study, exposed or unexposed in a cohort study

13. Total population CasesControls Present5001800 Absent5007200 100010000 Exposure odds500:5001800:7200 500 OR= 500 = 4.0 1800 7200

14. Unbiased sample of population 50% of Cases10% of Controls Present500 x 0.5 = Absent500 x 0.5 = Exposure odds OR==

15. Biased sample of population CasesControls Present500 x 0.6 =1800 x 0.1 = Absent500 x 0.4 =7200 x 0.1 = Exposure odds OR==

16. = 1.5 Bias = Observed odds cases 1.0 = 1.5 True odds cases 1.0

17. = odds exp/cases x [bias]odds exp/cases = True OR odds exp/controls x [bias]odds exp/controls

18. Biased sample of population CasesControls Present500 x 0.6 =1800 x 0.136= Absent500 x 0.4 =7200 x 0.091= Exposure odds OR==

19. = 1.0 x 1.5 = 1.5 odds exp/cases x [bias]1.0 = 4 odds exp/contl x [bias]1.0x 1.51.0 4.02.67

20. سوگرايي انتخاب در مطالعه ‌ هاي كيفي

21. Avoiding and detecting selection bias In case-control studies, Choose controls from the same “study-base” as cases. In cohort studies, the rate of loss to follow-up indicates the potential for selection bias. Comparison of the characteristics of those lost to follow-up with those persons remaining under follow-up, may indicate the potential consequences of any selection bias.

22. نمونه ‌ گيري در مطالعه ‌ مورد شاهد انتخاب جمعيت پايه : – اوليه – ثانويه

24. Counterfactual analysis is clear and practical approach for decomposition

25. سوگرايي انتخاب سوگرايي انتخاب وعلت رخداد آن را شرح دهد. سوگرايی انتخاب جبران شده را درک نمايد. نحوه ی مقابله با سوگرايي انتخاب را بداند.

26. مفهوم تحليل مقابل واقع بار ديابت Pr (D) Pr’(D) بار قابل اجتناب واقعمقابل واقع

27. Information Bias Information Bias: results from a systematic error in measurement thus leading to misclassification (in exposure or outcome category). A classic example is: recall bias, in which the ability to recall past exposure is dependent on case or control status. Cases may be more likely than controls to overstate past exposure

28. Diseased Exposed + - +-+- REFERENCE POPULATION STUDY SAMPLE The direction of the association is a function of which cell(s) are subjected to a higher or lower probability Eg...unexposed cases in this example tend to mistakenly report past exposure to a greater extent than do controls Cases Control Misclassification of EXPOSURE

29. Diseased Exposed + - +-+- REFERENCE POPULATION STUDY SAMPLEEg…cases in this are mistakenly classified as controls due to low sensitivity on a screening test Cases Control Misclassification of OUTCOME

30. Information Bias These errors result in misclassification of exposure and/or outcome status Terms: validity, sensitivity, specificity and reliability refer to classification of both disease and exposure status (and confounders)

31. Definition of Terms Related to Classification Validity: the extent to which a measurement measures what it purports to measure. –Sensitivity: the ability of a test to identify correctly those who have the disease (or characteristic) of interest. –Specificity: the ability of a test to identify correctly those who do not have the disease (or characteristic) of interest Reliability (repeatability): the extent to which the results obtained by a test are replicated in the test is repeated.

32. 1. Exposure Identification Bias Problems in the collection of exposure data 2 main examples: –Recall bias –Interviewer bias

33. 1.1 Recall Bias Most cited: inaccurate recall of past exposure (may be due to temporality, social desirability or diagnosis). If recall differs between cases and controls, misclassification is differential; If the error is of similar magnitude, then it is said to be non-differential

34. How to Prevent Recall Bias 1.Verification of exposure information from participants by review of pre-existing records 2.Selection of diseased controls and compensating this bias 3.Objective markers of exposure or susceptibility (for example- genetic markers). 4.Nested case-control studies allow evaluation of exposures prior to “case” status

35. 1.2 Interviewer Bias May occur when interviewers are not blinded to disease status. –They may probe more Interviewers may be biased toward the study hypothesis (or have other biases). –They may ignore protocols

36. 2. Outcome Identification Bias Problems in the collection of outcome measurements. Two main examples: –Observer bias –Respondent bias

37. 2.1 Observer Bias In a Cohort study: decision to classify outcome may be affected by knowledge of exposure status. Especially “soft” outcomes such as migraine, or psychiatric symptoms Eg: assignment of diagnosis of hypertensive end-stage renal disease (ESRD). Nephrologists sent case histories were twice as likely to diagnose “black” patients with ESRD than “white” patients”.

38. Preventing Observer Bias Mask observers in charge of classifying outcome with respect to exposure status Multiple observers

39. 2.2 Respondent Bias Most often examples are in case-control studies where biases are associated with identification of exposure. Eg: Parents may be more likely to identify having given their children aspirin in a case-control study of Reyes syndrome compared to population controls

40. 2.2 Respondent Bias In a Cohort study: respondents may respond with little consistency to un-standardized questions or to “subjective” questions. Eg. Questions about depression may be very subjective. A solution is to use a standardized instrument.

41. 3. The result of information bias: Misclassification Nondifferential misclassification Differential misclassification

42. 3.1 Nondifferential Misclassification Occurs when the degree of misclassification of exposure is independent of case-control status (vice-versa) Example: misclassification of HCV infection due to window period in a study looking at risk factors for HCV. Both the exposed and the unexposed are equally likely to be misclassified as unexposed.

43. Nondifferential Misclassification Example: misclassification of exposed subjects as unexposed in 30% of cases and 30% of controls No misclassification ExposureCasesControls Yes5020 No5080 OR= (50/50)/(20/80) or (50*80)/(50*20) = 4.0 30% Exposure misclassification in each group ExposureCasesControls Yes50-15=3520-6=14 No50+15=6580+6=86 OR= (35*86)/(65*14) = 3.3 Effect of non-differential misclassification with 2 exposure categories: to bias the OR toward the null value of 1.0

44. Application of sensitivity/specificity concepts in misclassification of exposure: schematic representation of true and misclassified relative odds. Sensitivity of exposure ascertainment= TP  (TP +FN) Specificity of exposure ascertainment= TN  (TN +FP) Cases Controls True Exp UnexpExpUnexp OR (pos) (neg)(pos) (neg) True results A C B C [A/C  B/D] Study total study total study MIS- Results cases controls classified OR Exp TP FP TP + FP = a TP FP TP + FP = b Unexp FN TN FN + TN = c FN TN FN + TN= d [a/c  b/d] Figure 4-4

45. Effects of nondifferential misclassification on the odds ratio -->Since the sensitivity and specificity values are the same for cases and control, the effect is nondifferential Cases Controls True exp unexp exp unexp OR true distribution (gold standard) 50 50 20 80 50/50  20/80 =4.0 Study distribution: Cases Controls Exposed 45 10 55 18 16 34 Unexposed 5 40 45 2 64 66 55/45  34/66 =2.4 sensitivity (exp) or specificity (unexp) 0.90 0.80 0.90 0.80 Misclassified OR Exhibit 4-3

46. Nondifferential misclassification of exposure: effects of sensitivity and specificity of exposure identification and of exposure prevalence in controls on a study’s OR (true OR=4.0) SensitivitySpecificityPrev of Exp in controls Observed OR 0.900.850.202.6 0.600.850.201.9 0.900.950.203.2 0.900.600.201.9 0.90 0.3683.0 0.90 0.202.8 0.90 0.0772.2 Table 4-5

47. True situation NoneLowHigh Cases 100200600 Controls 100 OR 1 40% high NoneLowHigh Cases Controls OR 1 40% high NoneLowHigh Cases Controls OR 1

48. True situation NoneLowHigh Cases 100200600 Controls 100 OR 126 40% high NoneLowHigh Cases 100440360 Controls 10014060 OR 13.16 40% high NoneLowHigh Cases 340200360 Controls 14010060 OR 10.82.5

49. 3.2 Differential Misclassification Occurs when the degree of misclassification of exposure (outcome) differs between the groups being outcome (exposure) groups Effect is: bias toward or away from the null

50. Effect of differential misclassification on the OR, in which, for Sensitivity Cases > Controls and, for specificity, Cases = Controls Cases Controls True exp unexp exp unexp OR true distribution (gold standard) 50 50 20 80 50/50  20/80 =4.0 Study distribution: Cases Controls Exposed Unexposed sensitivity (exp) or specificity (unexp) 0.96 1.00 0.70 1.00 Misclassified OR

51. Effect of differential misclassification on the OR, in which, for Sensitivity Cases > Controls and, for specificity, Cases = Controls Cases Controls True exp unexp exp unexp OR true distribution (gold standard) 50 50 20 80 50/50  20/80 =4.0 Study distribution: Cases Controls Exposed 48 0 48 14 0 14 Unexposed 2 50 52 6 80 86 48/52  14/86 =5.7 sensitivity (exp) or specificity (unexp) 0.96 1.00 0.70 1.00 Misclassified OR

52. Effect of differential misclassification on the OR, in which, for both Sensitivity and Specificity, Cases>Controls Cases Controls True exp unexp exp unexp OR true distribution (gold standard) 50 50 20 80 50/50  20/80 =4.0 Study distribution: Cases Controls Exposed 48 0 48 14 16 30 Unexposed 2 50 52 6 64 70 48/52  30/70 =2.1 sensitivity (exp) or specificity (unexp) 0.96 1.00 0.70 0.80 Misclassified OR