Lecture 7: Bias and Confounding in Epidemiological Studies

Question 1

How do you get from association to causation?

Answer 1

If bias, confounding, and random error have been ruled out as alternate explanations, then we can get causal inference.

Bias in Knowledge Use
Reporting and Publication Bias
Bias in Analysis and Inference
Information Bias
Selection Bias
Confounding
Random Error
Causal Effect

Question 2

Types of errors in epidemiological inference

Answer 2

Random Error and Systematic Error

Question 3

Random Error

Answer 3

• When a sample measurement is different from the true population value due to chance
• Random Error cannot be eliminated but we can reduce the severity through large sample size

Question 4

Major Sources of Random Error

Answer 4

Individual Biological Variation
Sampling Error
Measurement Error

Question 5

Individual Biological Variation

Answer 5

• there is a variation in the entity being studied
• caused by intra-individual and inter-individual differences
• ex. blood pressure
• address this error through using repeated measures

Question 6

Sampling Error

Answer 6

• sample size is too small and not representative of the population
• characteristics of the sample are different due to chance.
• addressed by having a large population size

Question 7

Measurement Error

Answer 7

• Occurs when there is inaccuracy in instrument or person operating the instrument
• error is due to chance because no measurement is perfectly accurate

Addressed by:
- using strict study protocols
- making sure investigators understand method being used
- making sure labs undergo quality control procedures

Question 8

What to consider for sample size calculations?

Answer 8

1. Level of statistical significance
2. Acceptable Error
3. Magnitude of Effect Under Investigation
4. Prevalence of disease in the population
5. Relative sizes of groups being compared

Question 9

Sample size in case-controls

Answer 9

• if disease is rare, select all cases of disease and sample of controls
• need to achieve a 4 to 1 ratio (that is when the maximum power is reached)

Question 10

Systematic Error

Answer 10

• Error that is not due to chance
• involved with something that the research has done in regard to the design and implementation of the study

Question 11

Bias

Answer 11

Systematic error that results in an incorrect/invalid measure of the association

Question 12

Two major sources of systematic error

Answer 12

Selection Bias
Information/Measurement Bias

Question 13

Selection Bias

Answer 13

• Systematic differences between people included and not included in the study
• cohort studies: error in selection of exposed and unexposed
• volunteer bias and differential loss to follow up are main sources for prospective
• case-controls: error in selection of cases and controls
• inclusion of controls that are representative of the population for case-control

Question 14

Selection bias may be due to..

Answer 14

Procedures used to select participants (healthy worker effect)
Factors that Influence continued participation in the study (long follow-up period)

Specific characteristics may affect motivation to participate and ability to participate:
- motivation to participate (worried about exposure)
- ability to participate (low SES, poor health)

Question 15

Avoiding Selection Bias

Answer 15

Selecting into the study:
- in procedures used to select
- sampling strategy should target person representative of broader population
- incentive to participate

Continuing in the study:
- Keep participants engaged in the research
- ask participants to provide secondary contact
- use tracing method

Question 16

Measurement Bias

Answer 16

• individuals in the study are systematically placed in the wrong exposure or outcome group
• flaw in measuring exposure, outcome, covariant which results in different information between comparison groups
• Results from systematically imperfect definitions of study variables or data collection methods

Question 17

Major sources of measurement bias

Answer 17

• recall bias
• observer bias

Question 18

Recall Bias

Answer 18

• subjects in the study have difficulty recalling information
• mainly in case-controls since you are interviewing the cases about their past controls
• can occur in cohort studies if asked about past exposures

Question 19

Avoiding Recall Bias

Answer 19

• use objective markers of exposure
• verify responses
• use diseased controls in case-control study (case are more likely to remember information)

Question 20

Proxy Respondents

Answer 20

• are not the subject themselves but someone close to the subject that can respond on their behalf
• are not going to have the most accurate information as they are not that person

Question 21

Observation bias

Answer 21

• interview might insert their subjective opinions
• occur in case-control studies as knowledge of disease status might influence questions about exposure
• can occur in cohort and experimental if they inquire about exposed and unexposed

Question 22

Avoiding Observation Bias

Answer 22

• mask interviewers
• conduct quality assurance activities with interviewers
• test reliability of interviewers’ data

Question 23

Misclassification

Answer 23

• error in the classification
• non-differential: degree of misclassification is same for study groups
• differential: degree of misclassification is different for study groups

Question 24

Confounding

Answer 24

• there is a third variable that could be an explanation for the association between the variables under study
• variable is a risk factor for the outcome
• variable is association with the exposure

Question 25

Effect of confounder

Answer 25

Association may be induced, strengthened, weakened, or eliminated. Impact depends on:
- strength of association between confounder and outcome
- strength of association between confounder and exposure
- prevalence of confounder

Question 26

Controlling confounders in the study design

Answer 26

• randomization
• restriction
• matching

Question 27

Limitations of randomization

Answer 27

only used in experimental studies

Question 28

Limitations of restriction

Answer 28

• difficult to find study subjects
• reduces generalizability

Question 29

Limitations of matching

Answer 29

• can’t match on more than a few confounders
• difficult to find appropriate controls
• once a variable is matched for, it can no longer be evaluated

Question 30

Controlling confounders in an analysis design

Answer 30

• stratification
• statistical modeling

Question 31

Limitations for stratification

Answer 31

• can only control for categorical confounders
• sample sizes may be too small

Question 32

Limitations of statistical modelling

Answer 32

• difficult for non-researchers to interpret
• requires a large sample size
• certain assumptions need to be met