Final: Lectures 17-18 Flashcards

0
Q

Definition of Bias

A
  • Systemic (non-random) error in study design or conduct leading to erroneous results.
  • Distorts the relationship (ass.) between exposure and outcome
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1
Q

What are the 3 aspects of a study do researchers evaluate before declaring a statistical association?

A
  • Check for bias
  • Check for confounding or effect modification
  • Check for statistical significane
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2
Q

T/F Bias can be fixed once it has already occurred (after study end).

A
  • False

* Prospective (pre-study) consideration and adjustment can minimize bias and its impact

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3
Q

When assessing for bias and its impact, investigators evaluate 3 components:

A
  1. Source/Type
  2. Magnitude/Strength: can account entirely for a weak ass. but is not likely to account for very strong ass.
  3. Direction: *Bias can over- or under-estimate the true measure of ass. (towards or away from the Null Hypothesis)
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4
Q

Information/Observation/Measurement-related biases

A
  • Any aspect in the way the researcher collects info, or measures/observes subjects, which creates a systematic difference between groups in the quality/accuracy of their info
  • Errors in measurement or classification
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5
Q

Selection-related biases

A
  • Any aspect in the way the researchers selects subjects which creates a systematic difference in the composition between groups
  • commonly seen when comparative groups not coming from same population/group or not being representative of full pop
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6
Q

Types of Selection Bias

A
  • Healthy-Worker Bias: can easily be seen in prospective Cohort studies
  • Self-Selection/Participant (Responder) bias: those that wish to participate may be different in some way to those that don’t volunteer or self-select to participate (may be base on education or income)
  • Control Selection bias: easily seen in Case-Control studies
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7
Q

Recall (reporting) bias

A
  • Subject-related variation (info bias): a differential level of accuracy/detail in provided info between study groups
  • Exposed or diseased subjects may have greater sensitivity for recalling their history or amplify their responses (Negative event tied to bad experience helps you remember, or profoundly positive)
  • Individuals can report their “effects” of exposure, disease symptoms or treatment differently b/c they are part of a study, “Hawthorne Effect”
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8
Q

Contamination bias

A
  • Subject-related bias: members of the control group accidentally, or outside of the study protocol, receive the treatment or are exposed to the intervention being studied
  • Not taking pills, taking other pills that react to the drug being tested ect.
  • Likely connected to interventional studies
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9
Q

Compliance Bias

A
  • Subject-related bias: groups being interventionally studied have different compliances
  • Not taking drugs as recommended due to side-effects, benefit, ect.
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10
Q

Lost to Follow-up bias

A
  • Subject-related bias: groups being studied have different withdrawal rates OR there are other differences between those that stay in the study and those that withdraw or are lost to follow-up
  • Differential vs Non-Differential
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11
Q

Can Cohort studies have lose to follow-up?

A

•Yes, with prospective, waiting for the disease to occur lost to follow-up

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12
Q

Interviewer (Proficiency) bias

A
  • Observer-related variation: a systematic difference in soliciting, recording, or interpreting on the part of their researcher
  • Interviewers knowledge may influence the structure, or tone, of questions or follow-up questions which may influence response from the study subject OR..
  • The interventions or treatments are not applied equally between groups due to skill or training differences of study personnel or differences in study procedure compliance by staff at different sites
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13
Q

Diagnosis/surveillance (Expectation) bias

A
  • Observer-related variation: Different evaluation/classification/diagnosis/ observation between study groups
  • Observes may have preconceived expectations of what they should find in examination/evaluation/follow-up
  • “Hawthorne-like Effect” from the researchers perspective
  • Kappa statistic, agreement between evaluators, making sure they ask the same question in the same way to each patient
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14
Q

Controlling for Bias

A
  • Select most precise, accurate, and medically-appropriate easures of assessment and evaluation/observation
  • Blinding/Masking
  • Use multiple sources to gather all info
  • Randomly allocate observers/interviewers for data collection (and train them! use technology!)
  • Build in as many methods necessary to minimize loos to follow-up
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15
Q

What is the source of info/observation/measurement bias?

A

•Misclassification (error in classifying either disease or exposure status, both)

16
Q

Non-differential (error in both groups equally) misclassification

A
  • Misclassification of exposure or disease which is unrelated to the other, depending on study design
  • Effect = for 2 category variables, bias can move the measure of ass. toward the null hypothesis, it attenuates your effect estimates of ass.
  • Ex. RR of .3 moves to .7 (attenuation towards the null)
  • Ex. OR of 1.9 moves to 1.2 (attenuation towards the null)
17
Q

Differential (error in one group differently than other)

A
  • Misclassification of exposure or disease is related to the other, depending on study design
  • Effect = Bias can move the meausre of ass. in either direction in relation to the null, it can inflate or attenuate your effect estimates of ass.
  • Ex. RR of .8 moves to .2 or 1.4 to 2.1 (inflation from null)
  • Ex. OR of 2.3 moves to 1.1 or .6 moves to .9 (attenuation towards null)
18
Q

OR =

A

•ad/bc

19
Q

T/F Non-Differential misclassification has equal changes in numbers in the control and cases.

A

•True, Look for balances and equal differentiation