Observation Bias (Information Bias)
Biased measure of association due to incorrect categorization.
Diseased
Not Diseased
Exposed
The Correct
Classification
Not Exposed
Observation Bias (Information Bias)
Biased measure of association due to incorrect categorization.
Diseased
Not Diseased
Exposed
Errors in
Classification
Not Exposed
Misclassification Bias
Subjects are misclassified with respect to their risk factor
status or their outcome, i.e., errors in classification.
Non-differential Misclassification (random): If
errors are about the same in both groups, it Errors
tends to minimize any true difference between
=
the groups (bias toward the null).
Differential Misclassification (non-random):
If information is better in one group than
another, the association maybe over- or
underestimated.
Errors
Errors
Errors
Non-Differential Misclassification
Errors
=
Errors
When errors in exposure or outcome status occur
with approximately equal frequency in groups being compared.
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?
Non-Differential Misclassification
Errors
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.”
“Null” means
no difference
0.3 0.5
1.0
Relative Risk
2
3
=
Errors
Differential
Misclassification
Errors
When errors in classification of exposure or
outcome are more frequent in one group.
•
•
•
Errors
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.
Recall Bias
Errors
Errors
(Differential)
Note: If the groups have the same % of
errors based on faulty memory, that’s
non-differential misclassification.
People with disease may remember exposures differently
(more or less accurately) than those without disease.
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?”
(Differential)
Interviewer Bias
(& recorder bias in record reviews)
Errors
Errors
Are you sure?
Think harder!
Systematic differences in soliciting,
recording, or interpreting information.
Interviewer
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.