CIfly can be used for a variety of tasks in graphical causal inference. Here, we discuss example applications and show how they can be solved transparently and efficiently with CIfly.

• Verifying adjustment sets

  Test whether a set of variables can be used for adjustment for a given CPDAG and sets of treatment and outcome variables.

  Graph type:

  CPDAG

  References:

  Perković et al. (2018)

• Optimal conditional instruments

  Find a graphically optimal conditional instrumental set for a given ADMG and a treatment and outcome variable.

  Graph type:

  ADMG

  References:

  Henckel et al. (2024a)

• Finding minimal d-separators

  Find a minimal d-separator for sets of variables X and Y, that is one for which no subset d-separates X and Y.

  Graph type:

  ADMG

  References:

  van der Zander, Liśkiewicz (2020)

• Parent adjustment distance

  Computing the parent adjustment distance for measuring the distance between two CPDAGs.

  Graph type:

  CPDAG

  References:

  Henckel et al. (2024b)

• Finding conditional instruments

  Compute conditional instrumental sets in ADMGs based on a sound and complete graphical criterion.

  Graph type:

  ADMG

  References:

  Henckel et al. (2024a); van der Zander, Liśkiewicz (2020)