References | Resources for Causal Reasoning in Health Services Research

From Association to Causation in Observational Studies: The Role of Tests of Strongly Ignorable Treatment Assignment. Rosenbaum Paul R. 2011
The Causal Foundations of Structural Equation Modeling. Pearl Judea. 2011
Attributable Fractions for Sufficient Cause Interactions. Vanderweele Tyler J. The International Journal of Biostatistics; 2010
Direct Effect Models. van der Laan Mark J., Petersen Maya L. The International Journal of Biostatistics; 2009

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Directed acyclic graph (DAG): Definition

Directed acyclic graph (DAG)
a graph in which nodes represent variables and arrows represent influence between the variables they connect without loops; an arrow drawn from variable $X$ to variable $Y$ represents a dependency of $Y$ on $X$ , and no dependency of $X$ on $Y$
Mediation: Definition

Mediation
production of effect through a third variable
Risk: Definition

Risk
probability of an event during a specified period of time
d-separation: Definition

d-separation
variables $X$ and $Y$ are said to be $d$ -separated, if all paths from $X$ to $Y$ are blocked. A path may be blocked by a set of variables $S$ , if the path contains at least one arrow-emitting variable that is in $S$ or if the path contains at least one collider that is not in S and has no descendent in $S$ . A collider is defined as a variable on a path such that the path enters and leaves via arrow heads. $X$ and $Y$ are, therefore, $d$ -separated conditional on $S$ , if $S$ blocks all paths between $X$ and $Y$ . X and Y are marginally independent when S contains the null set

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