SuSTaIn
About
News
Postgraduate degrees
Events
Research highlights
Jobs
Management
Statistics Group
Statistics Home
Research
Members
Seminars
Mathematics Home
External Links
APTS
Complexity science
Royal Statistical Society
International Society for Bayesian Analysis

Graphical Models for Inference Under OutcomeDependent Samplingby Vanessa Didelez, Svend Kreiner and Niels Keiding
We consider situations where data have been collected such that
the sampling depends on the outcome of interest and possibly further covariates,
as for instance in casecontrol studies. Graphical models represent
assumptions about the conditional independencies among the variables. By
including a node for the sampling indicator, assumptions about sampling
processes can be made explicit. We demonstrate how to read off such graphs
whether consistent estimation of the association between exposure and outcome
is possible. Moreover, we give sufficient graphical conditions for testing
and estimating the causal effect of exposure on outcome. The practical
use is illustrated with a number of examples.
