GENERAL THEORY FOR INTERACTIONS IN SUFFICIENT CAUSE MODELS WITH DICHOTOMOUS EXPOSURES

Area of Science:

• Causal inference
• Epidemiology
• Philosophy of science

Background:

• The sufficient-component cause framework models how sets of causes produce outcomes.
• Representations of causes and outcomes are often not unique.
• Understanding causal interactions is crucial for scientific explanation.

Purpose of the Study:

• To define and provide conditions for sufficient cause interactions and singular interactions.
• To analyze monotonic effects of causes on binary outcomes.
• To relate these concepts to statistical models and probability of causation.

Main Methods:

• Utilizing the sufficient-component cause framework for a binary outcome and multiple binary causes.
• Developing empirical and counterfactual conditions for interactions.
• Investigating conditions for monotonic cause-effect relationships.

Main Results:

• Conditions are established for the presence of sufficient cause interactions and singular interactions.
• The framework accommodates cases with none, some, or all causes affecting the outcome monotonically.
• The study demonstrates how any set of potential outcomes can be replicated.

Conclusions:

• The sufficient-component cause framework provides a robust method for analyzing complex causal relationships.
• The findings offer a deeper understanding of causal interactions and their implications.
• Connections are drawn to linear statistical models and Judea Pearl's probability of causation.