Critical Thinking - Lecture Twenty-Seven Flashcards

Confounding I

1
Q

Confounding

A

A mixing or muddling of effects when the relationship we are interested in is confused by the effect of something else – the confounder

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2
Q

Epi saying for confounding

A

Risk factors party together

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3
Q

Example given for confounding

A

If you tend to drink alcohol, you tend to smoker

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4
Q

When if confounding valid?

A

If groups equivalent for anything else associated with outcome

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5
Q

Three properties of potential confounder

A

Independently associated with the outcome
Independently associated with the exposure
Not on the causal pathway

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6
Q

Independently associated with the outcome

A

A risk (or protective) factor for the outcome regardless of exposure status

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7
Q

Independently associated with the exposure

A

Imbalance in distribution across exposure groups

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8
Q

Not on the causal pathway

A

Not how the exposure affects the outcome

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9
Q

What can confounding do?

A

Over/Under-estimatation of a true association, Change the direction of a true association and give appearance of an association when not one

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10
Q

Give appearance of an association when not one

A

Go from null to something else

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11
Q

Change direction of a true association

A

Risk factor becomes protective factor (and vice versa)

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12
Q

Harmful exposure: over-estimation

A

Confounding has resulted in an over-estimation of the true harmful effect of the exposure (association appears stronger than it really is, RR is ‘further away from the null’)

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13
Q

Harmful exposure: under-estimation

A

Confounding has resulted in an under-estimation of the true harmful effect of the exposure (association appears weaker than it really is, RR is ‘closer to the null’)

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14
Q

Beneficial exposure: over-estimation

A

Confounding has resulted in an over-estimation of the true protective effect of the exposure (association appears stronger than it really is, RR is ‘further away from the null’)

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15
Q

Beneficial exposure: under-estimation

A

Confounding has resulted in an under-estimation of the true protective effect of the exposure (association appears weaker than it really is, RR is ‘closer to the null’)

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16
Q

Identifying potential confounders

A

Collect information on all potential confounders and look for imbalance in potential confounder between groups

17
Q

Criterion of collecting information on all potential confounders

A

Use literature to identify known and suspected risk factors for outcome
Collect information on factors strongly associated with exposure, regardless if known risk factor

18
Q

Why collect information on all potential confounders

A

If you don’t measure it, difficult to do anything about it later

19
Q

What do randomisation, restriction and matching have in common?

A

All attempt to make groups being compared alike with regard to potential confounder(s)
Can’t assess association between potential confounder and outcome
Can’t assess whether actually a confounder

20
Q

When is randomisation used?

A

In randomised controlled trials

21
Q

Limitations of randomisation?

A

requires large sample size, needs equipoise and needs intention-to-treat analysis

22
Q

Restriction

A

Restrict sample to one stratum of potential confounder

23
Q

When is restriction used?

A

Can be applied to all study designs

24
Q

Limitations of restriction

A

Can reduce generalisability, reduces number of potential participants, potential for residual confounding with imprecisely measured (or broadly defined) confounders and usually only one potential confounder

25
Matching
Choose people for the comparison (control) group who have the same values of the potential confounding factor(s) as people in the exposed group (cohort studies) or case group (case-control studies)
26
When is matching used?
Usually in case-control studies; individual or frequency
27
Individual matching
Ratio of cases to controls
28
Frequency matching
Assure that cases and controls have the same distributions
29
Positives of matching
Useful for difficult to measure/complex potential confounders and can improve efficiency of case-control studies with small numbers
30
Limitations of matching
Individual matching can be difficult and limit number of potential participants and need special matched analysis for individual matching