Hierarchial causal models are described as pictorial representations of multiple regression equations. These models are particularly helpful for three reasons: (1) the formulation of problems in a path analytic framework forces a degree of explicitness that is often not present in research reports that rely solely on regression; (2) they provide a…

An author of a paper (EC 602 060) that presents two causal models of learning disabilities comments on his interest in the research, how the research design developed, limitations of the research, and the need for replication with other disability groups. (JDD)

Two causal models are presented to describe influences on the performance of students with learning disabilities. The first model associates reading and math with three domains: neuropsychological, linguistic, and social-behavioral. The second model involved relationships among selected individual variables and suggests that learning disability is…

Presented is an approach to causal models in which some or all variables are discretely measured, showing that path analytic methods permit quantification of causal relationships among variables with the same flexibility and power of interpretation as is feasible in models including only continuous variables. Examples are provided. (Author/IS)