Paths of association in epidemiological analysis: application to health effects of environmental exposures

Abstract

Conventional regression analysis is based on assumptions of bidirectional associations between pairs of independent variables. In a number of circumstances these assumptions are not plausible. Structural representation in conventional regression is based on a set of parallel paths between independent and dependent variables; when the implausible assumptions are excluded, a different structrual relation between the independent and dependent variables is found. It permits a series associative path between independent variables. Two criteria for modification of conventional multivariate analysis are presented. They are when bilateral symmetry among independent variables is implausible on the basis of a priori information, and when there are significant differences between zero order and first order partial correlation coefficients. When these criteria are applied, there may result a series-parallel matrix of associations. For analysis of such a matrix, the procedures of path analysis are appropriate. The concepts are illustrated with environmental examples, and path analytical computations are worked out for a set of data on social and environmental factors which affected infant mortality in England and Wales between 1928-1938.