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Wolfle, Lee M. – American Educational Research Journal, 1980
Path analysis is defined for explicitly formulating theory, and for attaching quantitative estimates to causal effects thought to exist on a priori grounds. The four basic kinds of path models are illustrated: (1) recursive; (2) block; (3) block-recursive and (4) nonrecursive. (Author/GDC)
Descriptors: Etiology, Mathematical Models, Path Analysis, Research Design
Wolfle, Lee M. – 1981
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…
Descriptors: Mathematical Models, Multiple Regression Analysis, Path Analysis, Research Methodology

Wolfle, Lee M. – Structural Equation Modeling, 1999
Researchers interested in linear causal models discovered that a genetic biologist, Sewall Wright, had laid the groundwork for these models over nearly 50 years. This annotated bibliography covers Wright's development of the method of path coefficients. (Author/SLD)
Descriptors: Annotated Bibliographies, Biology, Causal Models, Genetics

Wolfle, Lee M.; Ethington, Corinna A. – 1984
In his early exposition of path analysis, Duncan (1966) noted that the method "provides a calculus for indirect effects." Despite the interest in indirect causal effects, most users treat them as if they are population parameters and do not test whether they are statistically significant. Sobel (1982) has recently derived the asymptotic…
Descriptors: Algorithms, Computer Software, Hypothesis Testing, Path Analysis
Wolfle, Lee M. – 1980
An extension of the methods of path analysis to include studies of categorical data was described and exemplified in a causal study of college dropouts. The usual models and methods of causal (path) analysis were designed for the study of quantitative variables and are not appropriate when the variables under investigation are categorical.…
Descriptors: Academic Ability, Data, Data Analysis, Dropouts
Wolfle, Lee M. – 1982
Direct and indirect effects in decomposed zero-order correlations among variables in causal models are considered. Under certain circumstances, the components of the decompositions could be interpreted as direct, indirect, and spurious causal effects, plus a component called joint associations. The sum of the direct and indirect effects is the…
Descriptors: Elementary Secondary Education, Estimation (Mathematics), Mathematical Formulas, Mathematical Models
Ethington, Corinna A.; Wolfle, Lee M. – 1984
An extensive body of research indicates that men on the average achieve higher scores in mathematics than women. Despite this extensive research, conclusions about sex differences in mathematics achievement have suffered from various inadequacies in the use of measures of association among coursework experiences, sex, and other correlates of…
Descriptors: Correlation, Mathematics Achievement, Mathematics Instruction, Mathematics Skills
Robertshaw, Dianne; Wolfle, Lee M. – 1980
Data from the National Longitudinal Study of the High School Class of 1972 (NLS) including the 1976 follow-up were used to examine the effects of interrupting or delaying school attendance on the eventual educational attainment of white male students. Background variables include socioeconomic and other family characteristics. Achievement test…
Descriptors: Academic Achievement, Academic Aspiration, Academic Persistence, Dropouts