1. Observation Bias (Information Bias) Biased measure of association due to incorrect categorization. DiseasedNot Diseased Exposed Not Exposed The Correct Classification

2. Observation Bias (Information Bias) Biased measure of association due to incorrect categorization. DiseasedNot Diseased Exposed Not Exposed Errors in Classification

3. Non-differential Misclassification (random): If errors are about the same in both groups, it tends to minimize any true difference between the groups (bias toward the null). Errors Subjects are misclassified with respect to their risk factor status or their outcome, i.e., errors in classification. Errors = Differential Misclassification (non-random): If information is better in one group than another, the association maybe over- or underestimated. Misclassification Bias

4. Non-Differential Misclassification 1.Equally inaccurate memory of exposures in both groups. Example: Case-control study of heart disease and past activity: difficulty remembering your specific exercise frequency, duration, intensity over many years 2.Recording and coding errors in records and databases. Example: ICD-9 codes in hospital discharge summaries. 3.Using surrogate measures of exposure: Example: Using prescriptions for anti-hypertensive medications as an indication of treatment 4.Non-specific or broad definitions of exposure or outcome. Example: “Do you smoke?” to define exposure to tobacco smoke (vs. How much, how often, how long). CHD? When errors in exposure or outcome status occur with approximately equal frequency in groups being compared. Errors =

5. Effect: With a dichotomous exposure (e.g., smoking vs. non-smoking), non-differential misclassification minimizes differences & causes an underestimate of effect, i.e. “bias toward the null.” 0.3 0.5 1.0 2 3 “Null” means no difference Relative Risk Non-Differential Misclassification Errors =

6. Differences in accurately remembering exposures (unequal) Example: Mothers of children with birth defects will remember the drugs they took during pregnancy better than mothers of normal children (maternal recall bias). Interviewer or recorder bias. Example: Interview has subconscious belief about the hypothesis. More accurate information in one of the groups. Example: Case-control study with cases from one facility and controls from another with differences in record keeping. When errors in classification of exposure or outcome are more frequent in one group. Errors Differential Misclassification

7. Example: A case-control study of heart malformations in newborn infants. Cases group is mothers of infants with defects. Controls are mothers of normal infants. Both groups are asked about medication use during pregnancy. Of course, mothers of infants with defects will have already spent hours thinking about what might have caused the defect. “Was it something I took?” Note: If the groups have the same % of errors based on faulty memory, that’s non-differential misclassification. (Differential) Recall Bias People with disease may remember exposures differently (more or less accurately) than those without disease. Errors

8. (Differential) Interviewer Bias (& recorder bias in record reviews) Example: (The same case-control study on birth defects.) The interviewer believes that SSRIs are a cause of heart defects. Subconsciously, he probes harder when interviewing the mothers of the children with defects. “Are you sure you didn’t take any SSRIs? Perhaps you borrowed some from a friend.” -------------- Can also occur when reviewing records (e.g., the incidental appendectomy study. Systematic differences in soliciting, recording, or interpreting information. Are you sure? Think harder! Interviewer Errors