3.5.1 information bias

1. 1
Information bias
• Information bias
– Bias resulting from flawed definition of study
variables or measurement of study variables
– Results in erroneous classification of subjects with
regard to exposure and/or outcome – this is called
misclassification

2. 2
Information bias
• There are two types of misclassification:
– Non-differential misclassification
– Differential misclassification
• Definitions of these terms depend on the
variable being measured (i.e., exposure or
outcome)

3. Information bias
• Types of misclassification of outcome variables
– Non-differential misclassification of outcome
• The degree of outcome misclassification is not related to
exposure status
– Differential misclassification of outcome
• The degree of outcome misclassification depends on the
exposure status – this is a more serious problem
3

4. Information bias
• Types of misclassification of exposure
variables
– Non-differential misclassification of exposure
• The degree of exposure misclassification is not related to
outcome status
– Differential misclassification of exposure
• The degree of exposure misclassification varies by
outcome status – this is a more serious problem
4

5. Information bias
• Some specific exposure related information
biases
– Recall bias: occurs when participants are asked
about past exposure after the outcome in question
has occurred (or not), as often happens in case-
control studies
5

6. 6
Information bias
– The respondents’ memories vary according to
whether or not they experienced the outcome,
especially if the exposure is a commonly known risk
factor for the disease they have experienced
• Those with disease and the exposure more likely to recall
exposure
– Increased sensitivity
• Those with disease and not exposed more likely to report
exposure
– Reduced specificity
• Will explain use of sensitivity and specificity to quantify
information bias shortly

7. Information bias
• Some specific exposure related
information biases
– Recall bias example:
• Case-control study of gestational pesticide
exposure and offspring developmental delay
50

8. 8
Information bias
– Recall bias example (cont.):
• Mothers with developmentally delayed children
may more comprehensively recall their
exposures during pregnancy or may over-report
them, having spent time thinking about what
might have caused their child’s disability
• Control mothers with typically developing children
have not spent time pondering prenatal
exposures, and thus may be less likely recall
exposure

9. Information bias
• Some specific exposure related information
biases
– Interviewer bias: occurs when interviewers are not
blinded to participant disease status
9

10. Information bias
– Interviewer bias:
– Interviewers may question diseased and non-
diseased differently, for example emphasizing some
words or questions, or asking more clarifying
questions of those with disease in an attempt to
elicit information on the exposure
1
0

11. 1
1
Information bias
• Some specific outcome related information
biases
– Observer bias: occurs when observers/raters are
not blinded to exposure status (analogous to
interviewer bias, except affects disease
classification)
– Observers/raters may be more likely to count cases
among participants with high risk/exposure profiles

12. Information bias
• Some specific outcome related information
biases
– Observer bias example:
• A sample of nephrologists were sent patient case histories
with a simulated race randomly assigned to each case
• When the case history identified the patient as black, the
nephrologists were twice as likely to diagnose the patient
as hypertensive end-stage renal disease, as compared to
patients labeled white
1
2

13. Information bias
• Some specific outcome related information
biases
– Respondent bias: participants with high
risk/exposure profiles may be more likely to report
the outcome of interest
1
3

14. 1
4
Information bias
• Effects of non-differential versus differential misclassification
– In practice, it is impossible to correctly measure/collect all variable
some misclassification is inevitable
– Thus, it is important to thoroughly evaluate your exposure and
outcome definitions, study protocol, and data collection procedure
to evaluate what likely measurement error exists
– Then, think about the extent and direction of bias

15. 1
5
Information bias
• Non-differential misclassification
– Results in a bias toward the null when the exposure
or disease that is misclassified is binary
– For example, when a binary exposure is measured
with equal amount of error between case and
control groups, it washes out the exposure-outcome
association
– This is a conservative bias, and the investigator at
least knows that she/he is not presenting an
artificially large association

16. 1
6
Information bias
– Non-differential misclassification when there are
more than two categories of the exposure or
disease does not necessarily result in bias towards
the null
– Categorization of a variable that has non-differential
misclassification can generate differential
misclassification

17. 60
Information bias
• Differential misclassification of exposure or disease results in a
bias in an unpredictable direction – it may be toward the null or
away from the null
• It is possible to evaluate the bias on a case-by-case basis and
speculate the direction of the bias, however the possibility of bia
away from the null is problematic
• Generally considered a more serious problem than bias towards
the null because
– (a) the investigator does not know the direction of the bias with certainty, and
– (b) if the bias is away from the null, the investigator risks presenting an
artificially inflated effect estimate vs. an attenuated one

18. 1
8
Information bias
• Misclassification of a confounding variable
– Bias in an unpredictable direction

19. Information bias
• Numerical example of non-differential
misclassification
1
9

20. 2
0
Information bias
• Measures useful for quantifying information
bias
– Sensitivity
• P(classified positive|true positive)
– Specificity
• P(classified negative|true negative)

21. Information bias
• Case-control study data – the true distribution
of exposure
• OR=?
2
1

22. Information bias
2
2
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

23. Information bias
2
3
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

24. Information bias
• True positive (exposed)
cases = TP
• Classified positive
(exposed)
– = TPx(class pos|TP)
– = 80 x 0.9
• Classified negative
(unexposed)
– = TPx(1-(class pos|TP))
– = TPx(class neg|TP)
– = 80 x 0.1
– Or = TP-class. positive
2
4
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

25. Information bias
• True negative (unexposed)
cases = TN
• Classified positive
(exposed)
– = TNx(1-(class neg|TN))
– = TNx(class pos|TN)
– = 20 x 0.2
– Or = TN-class. negative
• Classified negative
(unexposed)
– = TNx(class neg|TN)
– = 20 x 0.8
2
5
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

26. Information bias
2
6
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

27. Information bias
2
7

28. Information bias
2
8

29. Information bias
2
9

30. 3
0
Information bias
• Non-differential because sensitivity and
specificity the same for cases and controls
• Resulted in bias towards the null
– True OR = 4
– Misclassified OR = 2.6

31. Information bias
• Numerical example of differential
misclassification
3
1

32. Information bias
• Case-control study data – the true distribution
of exposure
• OR=4
3
2

33. Information bias
3
3
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

34. Information bias
3
4
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

35. Information bias
3
5
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

36. Information bias
3
6
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

37. Information bias
80
Se:P(class. positive|true positive), Sp: P(class. negative|true negative)

38. 3
8
Information bias
• Differential because sensitivity and specificity
NOT the same for cases and controls
• This example resulted in bias away from the
null
– True OR = 4
– Misclassified OR = 5.7
• Can result in bias in either direction
– Exhibit 4-6 in Szklo – differential misclassification
resulting in bias towards the null

39. 3
9
Information bias
• Information biases types summary
– Non-differential misclassification of exposure
• Sensitivity and specificity of exposure
assessment not both 1.0 but the same for
diseased and non-diseased
– Differential misclassification of exposure
• Recall bias
• Interviewer bias
• Sensitivity and/or specificity of exposure
assessment NOT the same for diseased and
non-diseased

40. 4
0
Information bias
• Information biases types summary
– Non-differential misclassification of outcome
• Sensitivity and specificity not both 1.0 but the
same for exposed and unexposed
– Differential misclassification of outcome
• Observer bias
• Respondent bias
• Sensitivity and/or specificity NOT the same for
exposed and unexposed