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Epidemiology > Confounding and Bias > Flashcards

Confounding and Bias Flashcards

1
Q

if we survey NYC and top baseball team is Yankees, can we see it is the US’s fave team? Why not?

A

No, bc of selection bias

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2
Q

what 2 studies have forward directionality?

A

cohort
RCT

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3
Q

selection bias in cohort/RCT

A

ppl dropout or are lost to follow up (may be unequal in each group)

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4
Q

selection bias in case control

A

hospital controls may have higher alcohol intake (or a diff characteristic) than community controls

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5
Q

internal validity

A

proper group selection + lack of error in measurement

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6
Q

for internal validity, you must have accurate measurement of __, __, and __

A

for internal validity, you must have accurate measurement of exposure, outcome, and association btwn the two

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7
Q

external validity aka

A

generalizability

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8
Q

external validity

A

ability to generalize beyond a set of observations to a universal statement

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9
Q

confounding

A

an association btwn exposure and outcome is observed, BUT only as a result of a third variable

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10
Q

crude and adjusted measures of effect are not equal when __ is present

A

crude and adjusted measures of effect are not equal when a confounder is present

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11
Q

to be a confounder, the extraneous factor must:

A

1) be a risk factor of the disease
2) be associated with the exposure
3) not be an intermediate step in causal pathway btwn exposure and disease

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12
Q

3 ways to prevent confounding

A

1) randomization
2) restriction
3) matching

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13
Q

randomization attempts to have equal __ of __ in groups

A

randomization attempts to have equal distribution of confounders in groups

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14
Q

pros of randomization

A
  1. convenient
  2. cheap
  3. straightforward data analysis
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15
Q

cons of randomization

A
  1. need control over exposure and ability to assign subjects to study groups
  2. need large samples
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16
Q

randomization: how many conditions of confounding are not met?

A

1 of 2

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17
Q

restriction aims to prevent __ of __ in study groups

A

restriction aims to prevent variation of confounder in study groups

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18
Q

restriction provides complete control over __

A

restriction provides complete control over KNOWN confounders

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19
Q

restriction pros

A
  1. conceptually easy
  2. handles difficult to quantify variables
  3. can be used in analysis phase
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20
Q

restriction cons

A
  1. limits eligible subjects
  2. inefficient to screen and then not use people
  3. residual confounding if categories are not narrow enough
  4. limits generalizability
  5. can’t assess interaction (can’t stratify by age when age is narrow)
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21
Q

restriction: how many conditions of confounding are not met?

A

2

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22
Q

restriction is good for when confounder is __, but __

A

restriction is good for when confounder is quantitative, but hard to measure

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23
Q

restriction exmaple

A

sexual behavior and HIV
injectable drugs is a confounder, quantitative, but hard to measure
SO, just don’t include individuals who use injectable drugs

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24
Q

matching 2 types

A
  1. frequency matching
  2. individual matching
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25
Q

frequency matching

A

number of cases with match characteristics are equalized

26
Q

individual matching

A

pairing of 1 or more controls to each case based on sex, race, etc.

27
Q

cohort study matching

A

unexposed black matched to exposed black

28
Q

case-control matching

A

control age 50 to case age 50

29
Q

matching pros

A
  1. less ppl required than unmatched studies with same hypothesis
30
Q

matching cons

A
  1. expensive b/c extensive searching and record keeping is required
30
Q

matching cons

A
  1. expensive b/c extensive searching and record keeping is required
31
Q

2 types of analysis to control confounding

A
  1. stratification
  2. multivariate techniques
32
Q

stratification holds ___ constant

A

stratification holds confounder constant

33
Q

pros of stratification

A
  1. direct and logical strategy
  2. minimum assumptions required
  3. straightforward
  4. you may find an interaction
34
Q

cons of stratification

A
  1. strata may not have equal numbers
  2. multiple ways to form strata when using continuous variables
  3. hard with multiple confounders
  4. categorization causes information loss
34
Q

cons of stratification

A
  1. strata may not have equal numbers
  2. multiple ways to form strata when using continuous variables
  3. hard with multiple confounders
  4. categorization causes information loss
35
Q

multivariate statistics uses __ to estimate what association would be if __ wasn’t associated with __

A

multivariate statistics uses stats to estimate what association would be if confounder wasn’t associated with exposure

36
Q

pros of multivariate statistics

A
  1. continuous variables to do not need to be converted to categorical
  2. can control for multiple exposure variables at same time
37
Q

cons of multivariate statistics

A
  1. potential for misuse
38
Q

confounding issues

A
  1. can conclude a relationship when there’s not one
  2. can conclude there’s not a relationship when there is
39
Q

confounding is NOT __

A

confounding is NOT an error

40
Q

is an error to __

A

is an error to NOT control for confounding

41
Q

is an error to __

A

is an error to NOT control for confounding

42
Q

bias =

A

systematic design error that mistakes exposure’s effect on disease

43
Q

what kind of studies is bias a problem in?

A

ALL studies

44
Q

selection bias is flaws in

A

selecting participants

45
Q

information bias is flaws in

A

gathering info

46
Q

selection bias: relationship btwn disease and exposure is different from in those who

A

selection bias: relationship btwn disease and exposure is different from in those who were eligible but didn’t

47
Q

in study looking at cancer and coffee, the study sample over-represents…

A

in study looking at cancer and coffee, the study sample over-represents controls who don’t drink coffee (d)

48
Q

cohort study selection bias: lung cancer and abestos
who is over-represented?

A

unexposed with disease
lots of unexposed sick people at risk for lung cancers

49
Q

exclusion bias

A

if you apply different eligibility criteria to cases and controls
EX: Reserpine and breast cancer

50
Q

non-response bias is a type of __ bias

A

non-response bias is a type of selection bias

51
Q

non-response bias

A

responses may be higher in diseased or exposed
could show associated when tehre is none

52
Q

how to limit non-response bias?

A
  1. get people to respond
  2. characterize non-respondents as much as possible (they may be more likely to have certain traits)
53
Q

types of information bias

A

interview bias
surveillance bias
recall bias
reporting bias

54
Q

misclassification bias

A

misclassify unexposed as exposed is more common in cases

55
Q

misclassification bias dilutes __ and __

A

misclassification bias dilutes RR and OR

56
Q

interviewer/abstractor bias

A

interviewer probes cases more thoroughly for an exposure

57
Q

prevarication (lying) bias

A

participants have ulterior motives

58
Q

similar misclassification in cases and controls pushses association towards

A

1

59
Q

5 ways to prevent bias

A
  1. careful attention to sampling
  2. minimize non-reponse
  3. standardize measurements
  4. training and quality control
  5. blinding

Epidemiology (13 decks)

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