Bias and Confounding Flashcards Preview

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Flashcards in Bias and Confounding Deck (38)
1

if a study has a RR=4.3 and 95% CI (4.0-4.8) the association could be caused by:

random error

systematic error

true association between exposure and outcome

2

validity

absence of systematic error in a study result

3

what is a valid measure of association

will have same value as the true measure in the source population, except for error due to random variation

4

bias

extent to which a measure of association from a study differs from the true measure of association in the source population

5

T/F bias is for differences due to systematic and random errors

false: only systematic errors

6

T/F bias can make a study's conclusion invalid

true

7

internal validity

study result is valid with respect to the population under study
- study population
- source population

8

external validity

study result is valid to a wider population beyond to study and/or source population
AKA generalizability

9

study population

subjects in the study

10

source population

population from which the subjects were drawn

11

other populations (=target population)

populations to which we may want to generalize our results

12

2 types of bias

non-differential

differential

13

non-differential bias

equally affects groups

14

differential bias

affects one group more than another
- diseases are biased, but not the non-diseased

15

2 general sources of bias

selection

information

16

selection bias

sample is different from the population

17

information bias

error in measurement
AKA misclassification bias

18

confounding

unknown factor distorts the relationship between the exposure and outcome

19

selection bias in cross-sectional descriptive (prevalence) studies

sample would have more (or less) disease than true prevalence in the source population
- can over/underestimate the amount of disease in the source population

20

selection bias in case-control studies

case (diseased) or control (non-diseased) samples have more (or less) exposure than the diseased or non-diseased groups in the source population

21

selection bias in cohort studies

exposed or non-exposed samples have a higher (or lower) disease incidence than the exposed and non-exposed groups in the target populations

22

self-selection bias

based on volunteers-may not be representative of the population as a whole

23

diagnostic bias

diagnosis of disease may be influenced by the vet's knowledge of the exposure and their expectation of disease

24

how can you reduce diagnostic bias

have a clear, well-defines case definition

use as many objective parameters as possible

blinding of the exposure status of the animals

25

T/F if the error leads to misclassification they can lead to errors in the measure of association

true

26

information bias in cross-sectional (prevalence) studies

may result in prevalence estimate in the sample being different than the true prevalence in the target population

27

information bias in case control studies

error in measurement of the exposure in the diseased or non diseased may bias the association

28

how to reduce informational bias in case control and cross-sectional studies

evaluate accuracy of measuring tools and adjust estimates to reflect the error

29

information bias in cohort studies

error in measurement of the disease in the exposed or non-exposed

30

examples of informational bias

observer variation

deficiency of tools and technical errors

recall bias

reporting bias

31

confounding

distortion of the underlying relationship between an exposure and an outcome by a third factor

32

T/F third factor influences both the exposure and the outcome

true

33

T/F confounding is different than bias

false: confounding is a special type of bias

34

what 3 conditions must be met to be a confounder

associated with the exposure

associated with the outcome

not in the causal pathway between the exposure and the outcome

35

T/F before the study starts you can predict the confounder

true

36

how to reduce the confounder

match the study

restriction

randomization

37

confounding variable after study has been completed

stratify it

38

stratify

partition the results based on the confounding factor
ex: split sexes, type of practice etc