Argues that path analysis can clarify aspects of social processes but only if skilled practitioners use the models. The practitioners need to have better methodological training and statisticians need to contribute more to the training process. (RB)

Response to Freedman's critique of path analysis discusses appropriate ways to represent social processes in numerical form and the use of path analysis to achieve that goal. Discusses two main issues: the selection of variables and whether multiple regression can be used to model social processes. (RB)

Discusses the theoretical aspects of structural modeling rather than its applications. Considers the basic hypothesis in structural modeling and concludes that it can be an effective tool in some research contexts, though not all. (RB)

Suggests that improving the data collected for a study will lead to the development of better models to analyze that data. Also urges researchers to have a more critical attitude toward the literal interpretation of test results. (RB)

Comments on the uses of statistical analysis in social sciences within the context of Freedman's "As Other's See Us: A Case Study in Path Analysis." Points out that there is an unacknowledged gap between statistical principles and the data analysis that social scientists use. (RB)

Discusses the application of path analysis in the context of genetic epidemiology. Examines the coherence of model specification, plausibility of modeling assumptions, the interpretability and usefulness of the model, and the validity of statistical procedures. (RB)

Presents a review of path analysis techniques using Hope's (1984) comparative study of schooling and social mobility in Scotland and the United States as a case study. Path analysis has been used in the social sciences to untangle complex cause and effect relationships. The limits of path analysis as a way to analyze complex social phenomena are…