Lecture 4: Confounding & Effect Modification Flashcards Preview

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Flashcards in Lecture 4: Confounding & Effect Modification Deck (43)
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1

the best population to compare with, is themselves minus the event

counterfactual theory

2

counterfactual theory requires the assumption of?

exchangeability

3

lack of exchangeability in a population results in ?

confounding or
we are unable to compare

4

when we are assessing the associations of an exposure and outcome between two groups, what question are we asking ourselves regarding a true association?

are there alternative explanations to the association?

5

researchers evaluate 3 aspects of their study, before declaring a true association

1. check for confounding variables
2. check for bias
3. check for statistical significance

6

define 'confounding variables'

a 3rd variable that distorts an association between the exposure and outcome

an alternative explanation

7

what associations do confounding variables effect?

OR
HR
RR

8

simple definition of confounding

another explanation that appears to be the cause of the outcome, but it is not

9

in order for a variable to be considered a confounder, it must have 3 things

1. independent association with exposure
2. independent association with outcome
3. not directly in the causal-pathway

10

what does it mean to 'not directly be in the causal pathway' ?

the confounding variable is not a stepping stone between exposure and outcome

it is independent of both

11

a measure of association that ignores all other factors

CRUDE measure of association
or
unadjusted

12

DAG

direct acyclic graph

13

if confounding is present, how do you go about knowing if it is present?

you must test and calculate for confounding

14

step 1 in testing for confounding

calculate crude RR
also called unadjusted RR

15

step 2 in testing for confounding

calculate OR for each individual strata of the 3rd variable

16

step 3 in testing for confounding

compare the crude vs. adjusted measures

17

when comparing calculations, what tells you if the 3rd variable is a confounder?

compare crude vs. adjusted
if >15% different === confounder

18

3 steps in testing for confounding

1. find crude RR
2. fund adjusted RR for each strata
3. compare crude vs. adjusted

19

what are the 2 main impacts of confounding variables?

magnitude of association
direction of association

20

what is the purpose of controlling for confounders?

to get a more accurate measure of association

21

at what 2 points in a research study can you control for confounding?

study design stage
analysis of data stage

22

what are 3 ways to control for confounding in the study design stage?

randomization
restriction of population
matching of participants in each group

23

what are 2 ways to control for confounding in the analysis of data stage?

this is after data has been collected
1. stratification
2. multivariate statistical analysis

24

2 important weaknesses of using randomization to control for confounders

must have a large sample size
practical only for interventional studies

25

weaknesses of using restriction for confounder controlling.

narrow restriction criteria limits who can be a subject
can negatively impact generalizeability

26

strengths of randomization

will large N, it is successful
stratified version precisely assures equal-ness

27

strengths of restriction

convenient, cheap
does not negatively impact internal validity

28

weaknesses associated with matching

difficult to do, time, expensive
only controls for confounders that are matched for

29

strengths of matching

greater analytic efficiency

30

strengths of stratification

straight forward, enhances understanding of data