Bias and Confounding

Question 1

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

Answer 1

random error

systematic error

true association between exposure and outcome

Question 2

validity

Answer 2

absence of systematic error in a study result

Question 3

what is a valid measure of association

Answer 3

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

Question 4

bias

Answer 4

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

Question 5

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

Answer 5

false: only systematic errors

Question 6

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

Answer 6

true

Question 7

internal validity

Answer 7

study result is valid with respect to the population under study

• study population
• source population

Question 8

external validity

Answer 8

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

Question 9

study population

Answer 9

subjects in the study

Question 10

source population

Answer 10

population from which the subjects were drawn

Question 11

other populations (=target population)

Answer 11

populations to which we may want to generalize our results

Question 12

2 types of bias

Answer 12

non-differential

differential

Question 13

non-differential bias

Answer 13

equally affects groups

Question 14

differential bias

Answer 14

affects one group more than another

- diseases are biased, but not the non-diseased

Question 15

2 general sources of bias

Answer 15

selection

information

Question 16

selection bias

Answer 16

sample is different from the population

Question 17

information bias

Answer 17

error in measurement

AKA misclassification bias

Question 18

confounding

Answer 18

unknown factor distorts the relationship between the exposure and outcome

Question 19

selection bias in cross-sectional descriptive (prevalence) studies

Answer 19

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

Question 20

selection bias in case-control studies

Answer 20

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

Question 21

selection bias in cohort studies

Answer 21

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

Question 22

self-selection bias

Answer 22

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

Question 23

diagnostic bias

Answer 23

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

Question 24

how can you reduce diagnostic bias

Answer 24

have a clear, well-defines case definition

use as many objective parameters as possible

blinding of the exposure status of the animals

Question 25

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

Answer 25

true

Question 26

information bias in cross-sectional (prevalence) studies

Answer 26

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

Question 27

information bias in case control studies

Answer 27

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

Question 28

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

Answer 28

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

Question 29

information bias in cohort studies

Answer 29

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

Question 30

examples of informational bias

Answer 30

observer variation deficiency of tools and technical errors recall bias reporting bias

Question 31

confounding

Answer 31

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

Question 32

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

Answer 32

true

Question 33

T/F confounding is different than bias

Answer 33

false: confounding is a special type of bias

Question 34

what 3 conditions must be met to be a confounder

Answer 34

associated with the exposure associated with the outcome not in the causal pathway between the exposure and the outcome

Question 35

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

Answer 35

true

Question 36

how to reduce the confounder

Answer 36

match the study restriction randomization

Question 37

confounding variable after study has been completed

Answer 37

stratify it

Question 38

stratify

Answer 38

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