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Su et all, 2012 (Problem (Confounding Variable (Solution (Design…
Su et all, 2012
Problem
Confounding Variable
Solution
Design
Stratification
Matching
Cohort Restriction
Randomization
Covariate Imbalance (High Dimension)
Solution:
Covariate Adjustment
Over-adjustment
Confounder is uncollected in the data or excluded from the model
Under-adjustment
A mediator is mistakenly considered as a confounder and included in the model for adjustment.
Controlling for a collider that correlates with both the treatment and the outcome via an "M-diagram"
Analysis
ANCOVA:
analysis of covariance
DAG:
directed acyclic graph
Interaction (Effect modification/moderation)
Problem:
Different treatment effects at different levels or values of covariates.
Hard to interpret
Change direction/degree of its causal inference on the outcome:
Type
Non - linear Interaction
Quantitative Interaction
1st, 2nd, higher order interaction
Qualitative Interaction
Treatment- by- covariate interaction:
Directional change in terms of treatment preference
Subgroup analysis:
Definition
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Extract the maximum amount of information
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