The Logic Of Causal Order by James A. Davis

By James A. Davis

This monograph isn't statistical. It appears as a substitute at pre-statistical assumptions approximately based variables and causal order. Professor Davis spells out the logical rules that underlie our principles of causality and explains the way to notice causal path, regardless of the statistical method used. He stresses all through that wisdom of the "real global" is critical and many times demanding situations the parable that causal difficulties will be solved by means of statistical calculations by myself.

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A slope coefficient is a number that tells us how much a dependent variable increases per unit increase in the independent variable. ) For example, assume it is really true that each additional hour of study increases one's score on the final exam by one and one half points (on the average). 5 when the units are exam points and hours. Similarly, one might have slopes for the effects of TV advertising on sales volume, the effect of years of schooling on occupational prestige, the effect of group size on conformity, and so forth.

We will also, however, find a cross-sectional statistical association between the heights of brothers and sisters. That slope is totally spurious. Nothing about a brother's height has a causal effect on his sister's height. What actually does produce statistical association in the absence of any causal flow? It's quite simple, as shown in this example: (1) Taller fathers produce taller sons (causal flow). (2) Taller sons will be associated with taller fathers (spurious slope produced by 1). (3) Taller fathers produce taller daughters (causal flow).

If all the negative signs go away, the system is consistent. In system a of Figure 9, after we reverse poles for X3, all arrows are positive. In system b, however, we reverse X3, which brings the negative arrows down from three to two. Then we reverse X4. This leaves us with one negative arrow (d) but there are no further changes that would decrease the number of arrows. Rule 6: A system is inconsistent if at least one pair of variables has both positive and negative signs among its direct, indirect, and spurious effects.

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