EBM 4 ; inference Flashcards
when determining the association between E (exposure) 7 D (disease) there are 5 possibilities that describe and explain the relationship
result could be due to;
- CHANCE (p values)
- reversible causality
- causal
- bias
- confounders
correlation
linear regression
C; how 2 continuous variables change together
(-1 to +1)
- MEASURES STRENGTH OF RELATIONSHIP
LR; relationship between one variable and another
MEASURES CHANGE IN OUTCOME PER UNIT CHSNGE IN THE EXPOSURE
y = a + bx
y ; outcome
x ; exposure
a ; y intercept
b ; slope
confounder
- what?
- 3 features
- another risk factor of a disease 3 features - must be associated with the exposure of interest - must be a risk factor of the disease - must NOT be in the causal pathway
how to reduce the effect of confounders
- RCT ; Randomised ; should mean exposure ; no relationship with cofounders (not v sure WHY THO)
CONTROL IN ANALYSIS
eg STRATIFICATION ;
- estimate OR for different strata
- keep levels of confounder constant so only exposure of interest levels are changing
- average out OR using some sort of equation
to control the effect of a no. of confounders
use REGRESSION MODELS
- used in associations where the outcome is binary (presence or absence of disease)
- v similar to line go regression except y value is binary, not continuous
- thus the relationship is ; how x increases and how this affects whether outcome is more likely to be absence or presence of disease
BIAS -
- 3types
- within each type you can have ?
1) - selection bias ; occurs in the selection of participants
2) - loss to follow up bias ; participants drop out
3) - measurement bias ; bias in measuring exposure & outcome ;
- performance bias ; occurs when 2 groups in a study are not treated equally e.g. placebo group given extra interventions etc
- detection bias ; when some participants are less likely to report outcomes etc
selection bias ; non differentiated selection bias or differentiated selection bias
NON DIFFERENCIATED SELECTION BIAS
- if any errors in selecting participants occurs equally between the 2 groups then the association between E & D is UNBIASED
DIFFERENCIATED SELECTION BIAS
- if the errors in selecting participants is not equal between the 2 groups then the association is biased and the association will be under or over biased
Measurement bias ; NON DIFFERENCIATED MEASUREMENT BIAS & MISSCLASSIFICATION & DIFFERENCIATED MEASUREMENT BIAS & MISSCLASSIFICATION
N.D.M.B&. MC
- measurement errors which lead to misclassification are equal in all groups then association will be underestimated as usually these errors make the groups more similar.
D.M.B & MC.
- measurement errors lead to misclassification occurs unequally in groups
- association may be over or under estimated - NOT GOOD
BIAS IN
- RCT
- cohort studies
- CASE CONTOL
RCT; mentioned above
COHORT;
- differential measurement bias is unlikely in a PROSPECTIVE CS since exposure is measured before outcome
CASE CONTROL STUDIES;
- recall bias ; errors in participants recalling their exposure or non exposure to something e.g. depressed cases are more likely to talk about being bullied than non depressed people i.e. controls
- interviewee bias; some interviewers will be more likely to get info out of participants etc
- also danger of REVERSE CAUSALITY
BRADFORD HILL CRITERIA
- temporal sequence ;
is it def causal and not reverse causality - strength of association ;
stronger the RR the more likely the relationship is causal - consistency of relationship ; if diff ppl did the study with diff participants would they get the same results ?
- biological gradient ie dosage compensation ; with increased exposure does risk of disease increase - more believable
- specifity ; exposure and disease association must be specific - specific outcome not multiple
- coherence ; explanation for the association
- reversibilty ; RCT evidence etc