Philosophers and scientists have maintained that causation, correlation, and partial correlation are essentially related. These views give rise to various rules of causal inference. This essay considers the claims of several philosophers and social scientists for causal systems with dichotomous variables. In section 2 important commonalities and differences are explicated among four major conceptions of correlation. In section 3 it is argued that whether correlation can serve as a measure of A's causal influence on B depends upon the conception of (...) causation being used and upon certain background assumptions. In section 4 five major kinds of partial correlation are explicated, and some of the important relations are established among two conceptions of partial correlation, the conception of screening off, the conception of partitioning, and the measures of causal influence which have been suggested by advocates of path analysis or structural equation methods. In section 5 it is argued that whether any of these five conceptions of partial correlation can serve as a measure of causal influence depends upon the conception of causation being used and upon certain background assumptions.The important conclusion is that each of the approaches (considered here) to causal inference for causal systems with dichotomous variables stands in need of important qualifications and revisions if they are to be justified. (shrink)

Two kinds of causal inference rules which are widely used by social scientists are investigated. Two conceptions of causation also widely used are explicated — the INUS and probabilistic conceptions of causation. It is shown that the causal inference rules which link correlation, a kind of partial correlation, and a conception of causation areinvalid. It is concluded anew methodology is required for causal inference.

In her paper entitled "Causal Laws and Effective Strategies" (1979), Cartwright sets out to establish the connection between laws of association and causal laws. In part Cartwright is trying to show the sense in which a cause increases the probability of its effect, and to explain what causal laws assert by giving an account of how causal laws are related to certain kinds of statistical laws. In section II we explicate the essential features of Cartwright's for- mulation and in section (...) III we argue that there are several reasons for believing that Cartwright's formulation is inadequate and must be rejected. Nonetheless, we believe Cartwright's formulation does contain two key insights into the nature of causation. In section IV we use these two insights to sketch out the key features of an alternative formulation that holds the certain laws of association are necessary conditions for causal laws. The alternative formu- lation, we believe, explains what it means to say a cause increases the probability of its effect. (shrink)