In
statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a s ...
and
causal graphs, a variable is a collider when it is causally influenced by two or more variables. The name "collider" reflects the fact that in
graphical model
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. Graphical models are commonly used in ...
s, the arrow heads from variables that lead into the collider appear to "collide" on the
node
In general, a node is a localized swelling (a "knot") or a point of intersection (a vertex).
Node may refer to:
In mathematics
* Vertex (graph theory), a vertex in a mathematical graph
*Vertex (geometry), a point where two or more curves, lines ...
that is the collider.
They are sometimes also referred to as inverted forks.
The causal variables influencing the collider are themselves not necessarily associated. If they are not adjacent, the collider is ''unshielded''. Otherwise, the collider is shielded and part of a triangle.
The result of having a collider in the
path
A path is a route for physical travel – see Trail.
Path or PATH may also refer to:
Physical paths of different types
* Bicycle path
* Bridle path, used by people on horseback
* Course (navigation), the intended path of a vehicle
* Desir ...
is that the collider blocks the association between the variables that influence it.
Thus, the collider does not generate an unconditional association between the variables that determine it.
Conditioning on the collider via
regression analysis, stratification, experimental design, or sample selection based on values of the collider creates a non-causal association between X and Y (
Berkson's paradox
Berkson's paradox, also known as Berkson's bias, collider bias, or Berkson's fallacy, is a result in conditional probability and statistics which is often found to be counterintuitive, and hence a veridical paradox. It is a complicating factor ar ...
). In the terminology of causal graphs, conditioning on the collider opens the path between X and Y. This will introduce bias when estimating the causal association between X and Y, potentially introducing associations where there are none. Colliders can therefore undermine attempts to test causal theories.
Colliders are sometimes confused with
confounder
In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlation ...
variables. Unlike colliders, confounder variables ''should'' be controlled for when estimating causal associations.
To detect and manage collider bias, scholars have made use of
directed acyclic graphs
In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called ''arcs''), with each edge directed from one ...
.
Randomization and quasi-experimental research designs are not useful in overcoming collider bias.
See also
*
Causality
*
Causal graphs
*
Confounding
In causal inference, a confounder is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlatio ...
*
Directed acyclic graph
In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called ''arcs''), with each edge directed from one ...
*
Selection bias
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population inte ...
*
Path analysis
*
Bad control
In statistics, bad controls are variables that introduce an unintended discrepancy between regression coefficients and the effects that said coefficients are supposed to measure. These are contrasted with confounders which are "good controls" and n ...
References
{{reflist
Epidemiology
Independence (probability theory)
Graphical models
Causal inference