Quiz

Question 1

Confounding definition

Answer 1

confusion, or mixing, of effects; the effect of the exposure of interest is distorted because the effect of an extraneous factor is mistaken for or mixed with the actual exposure effect

Question 2

Confounding occurs when…

Answer 2

an extraneous variable, either partially or completely accounts for an apparent association between study variable and outcome

Question 3

primary prevention (association)

Answer 3

causal association between the risk factor and disease must exist

Question 4

secondary prevention (association)

Answer 4

association may either be causal or statistical: the association may be confounded

Question 5

three ways of thinking about confounding

Answer 5

Classical approach, collapsibility approach, and counterfactual approach

Question 6

classical approach to confounding criteria for confounding

Answer 6

1) must be a risk factor for the disease independent form the study exposure
2) must be associated with the exposure under study in the source population
3) must not be a result of the exposure- not an intermediate variable in the causal pathway between the exposure and the disease

Question 7

exceptions to the criteria for confounding under the classical approach

Answer 7

1)random statistical association due to sampling variability
2) marker of unmeasured confounder
3) confounder is an intermediate variable, but question is whether other causal pathways exist

Question 8

Collapsibility approach to confounding criteria

Answer 8

the effect measure is homogenous across the strata defined by the confounder
collapsibility is the equality of stratum-specific measures of effect with the crude, unstratified measure

Question 9

counterfactual model approach to confounding

Answer 9

theoretical approach for defining the ideal comparison group; considers what the risk of the outcome would have been in the same exposed individuals if exposure had been absent

Question 10

restriction (to control for confounding in design stage)

Answer 10

confounding cannot occur if the distribution of the potential confounding factors do not vary across exposure or disease categories

Question 11

matching (to control for confounding in design stage)

Answer 11

selecting subjects according to the value of suspected confounder to ensure equal distribution among study groups

Question 12

matching in cohort studies

Answer 12

matching unexposed to exposed without regard to disease status

Question 13

matching in case-control status

Answer 13

matching non-diseases to diseased subjects

Question 14

control confounding in analysis stage

Answer 14

stratification; multivariable analysis; propensity scores; marginal structural models; direct acyclic graphs

Question 15

stratification

Answer 15

evaluating the association between exposure and disease within homogenous categories of the confounding variable

Question 16

traditional multivariable analysis

Answer 16

can handle large numbers of confounders at once; based on statistical regression models; selection of potential confounders based on a prior knowledge, evaluation of data, and best judgment of the investigator, NOT on statistical significance

Question 17

conditional confounding

Answer 17

a presumed confounder may be cofounded by other variables

Question 18

residual confounding

Answer 18

adjustment does not completely remove the confounding effect due to a given variable or set of variables

Question 19

collinearity (confounding)

Answer 19

excessive correlation between confounder and exposure of interest

Question 20

biological interaction

Answer 20

co-participation in a causal mechanism of two or more component causes

Question 21

statistical interaction

Answer 21

effect modification: effect measure modification; heterogeneity of effects; subgroup effects and statistical interaction

Question 22

interaction- heterogeneity definition

Answer 22

the effect of risk factor (A) on the risk of an outcome (Y) varies according to the levels of a third variable (Z)

Question 23

interaction - statistical interaction/joint effects definition

Answer 23

the measure of association when both risk factors are present is different than what would be expected form combining their individual effects

Question 24

interaction (general knowledge)

Answer 24

reciprocity of interaction; goal is to identify and report

Question 25

additive interaction

Answer 25

absolute difference or attributable risk model (Cohort study ONLY)

Question 26

multiplicative interaction

Answer 26

relative difference or ratio model

Question 27

quantitative interaction

Answer 27

when the association between factor A and outcome Y exists and is of the same direction in each stratum formed by Z, but the strength of the association varies across strata

Question 28

Qualitative interaction

Answer 28

the effects of A on the outcome Y are in opposite directions according to eh presence of the third variable Z or when there is an association in one strata formed by Z but not in the other

Question 29

cumulative incidence

Answer 29

proportion of the population at risk that will develop an outcome in a given period of time (time is not part of calculation)

Question 30

incidence rate

Answer 30

rate at which new cases occur per unit of time (time is part of calculation)

Question 31

Attributable risk

Answer 31

how much of the disease in people who are exposed is due to the exposure
AR=CIe-CInoe)

Question 32

population attributable risk

Answer 32

how much of the disease in the population is due to the exposure
PAR=CItoalpop-CInoE

Question 33

cohort study requirements

Answer 33

1) cohort members must meet criteria for being at risk of the disease
2) subjects initially free of disease under study
3) subjects are classified by the exposure status
4) subjects are followed prospectively over time for incidence of disease
5) incidence of outcome is compared by exposure status
6) usual measured of association are ratios of incidence proportion or rates or SMRs, SIRs

Question 34

select comparison groups-cohort

Answer 34

unexposed, internal comparison, external comparisons

Question 35

counterfactual example definition

Answer 35

risk of disease in the exposed if they had never been exposed

Question 36

etiologically relevant time window (cohort)

Answer 36

period of time during which an exposure is capable of causing disease

Question 37

lag time

Answer 37

how soon after exposure would you expect to see the disease

Question 38

information bias in cohort study

Answer 38

misclassification of exposure at baseline; changes in exposure status over time; ascertainment of outcomes during follow-up

Question 39

immortal time bias

Answer 39

assignment of exposure during a time when the participant is considered ‘immortal’
among exposed, duration of exposure increases during follow-up