Graphical Models for Inference Under Outcome-Dependent Sampling

Details Graphical Models for Inference Under Outcome-Dependent Sampling Graphical Models for Inference Under Outcome-Dependent Sampling

2011-01-05

arxiv.org/abs/1101.0901v1

Statistical Science 2010, Vol. 25, No. 3, 368-387

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/10-STS340 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M

Scientific paper

10.1214/10-STS340

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 case-control 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.

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