dag.adjust {dagR}

Adjust an existing DAG for covariables.

Description

Looks for associations introduced by adjusting for the covariables specified, then looks for biasing paths, and finally evaluates these paths.

Usage

dag.adjust(dag, A = c())

Arguments

dag

The DAG to be adjusted (or evaluated).

A

Vector indicating the adjustment set. The numbering is according to the nodes vector of the DAG, which is shown e.g. in the legend of a DAG drawn by dag.draw. This numbering is different (+1) from the one used in dag.init, because the nodes vector also contains the exposure at position 1 (in contrast to the covariables vector used in dag.init)!

Details

If the adjustment set is empty, the function only looks for biasing paths and evalutes these.

Value

A DAG with the adjustment set A, and possibly with additional associations introduced by adjustment, biasing paths found, and the status of these.
If adjustment set is not empty, searchType and searchRes are set to NULL.

Note

CAVE: Do not apply this to an already adjusted DAG, since this might not be handled appropriately (see documentation of dag.adjustment called by dag.adjust).

Author(s)

Lutz P Breitling <[e-mail]>

References

Breitling LP (2010). dagR: a suite of R functions for directed acyclic graphs. Epidemiology 21(4):586-587.
Breitling LP, Duan C, Dragomir AD, Luta G (2022). Using dagR to identify minimal sufficient adjustment sets and to simulate data based on directed acyclic graphs. Int J Epidemiol 50(6):1772-1777.
Greenland S, Pearl J, Robins JM (1999). Causal diagrams for epidemiologic research. Epidemiology 10(1):37-48.

See Also

dag.adjustment, find.paths, eval.paths