confounding

Question 1

what are confounders

Answer 1

they’re associated with the exposure and the outcome

Question 2

ways to deal with confounding

Answer 2

design stage - randomisation, restriction or matching (in case-control study)
analysis stage - stratification (split analysis by age group for example), standardisation/regression - building a statistical model

Question 3

why would patients be allocated randomly to 2 groups

Answer 3

to reduce the effect of confounders

control unknown confounding variables

Question 4

what does it mean if randomisation is stratified by diabetic status and why would it be done

Answer 4

all people with diabetes are divided equally

so any effect would not be as a result of differing numbers of diabetics

Question 5

confounding variable

Answer 5

a factor that is associated with exposure and outcome of interest
eg age, smoking, socioeconomic deprivation

Question 6

randomisation

Answer 6

ensuring both group have similar proportions of confounding variables

Question 7

regression

Answer 7

control confounding
analysis stage
statistical modelling is used

Question 8

restriction

Answer 8

control confounding

only include people without pre-existing illnesses

Question 9

standardisation

Answer 9

confounding
analysis
used to produce SMR

Question 10

stratification

Answer 10

control confounding
at analysis stage
risks calculated separately for each category of confounding variable