Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models…

One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant…

Problem Statement: A literature analysis revealed that contact disturbances, self-esteem and life satisfaction have been examined in different studies separately. In particular, the researchers observed that the studies conducted on Gestalt contact disturbances are limited in number. In this study, the variables of contact disturbances,…

In this study, structural equation modeling (SEM) is applied to an instrument assessing students' understanding of chemical change. The instrument comprised items on understanding the structure of substances, chemical changes and their interpretation. The structural relationships among particular groups of items are investigated and analyzed using…

The objective of this study is to analyze the relationship between preservice teachers' time and study environment management, effort regulation, self-efficacy beliefs, control of learning beliefs and metacognitive self-regulation. This study also investigates the direct and indirect effects of metacognitive self-regulation on time and study…

Little is known about the influence of language background in problem-based learning (PBL) tutorial groups on group processes and students' academic achievement. This study investigated the relationship between language background, secondary school score, tutorial group processes, and students' academic achievement in PBL. A validated tutorial…

D. B. Rubin's model for causal inference in experiments and observational studies is enlarged to analyze the problem of "causes causing causes" and is compared to path analysis and recursive structural equations models. A special quasiexperimental design, the encouragement design, is used to give concreteness to the discussion by…

Discusses linear structural relations, Two Stage Least Squares, and path analysis as statistical procedures that sometimes permit causal inferences from correlational findings. Even though two variables cannot be interpreted causally due to a possible but unknown third variable, these methods are appropriate for handling models with correlated…

The logical flaw of using the methods of path analysis and structural equation modeling to make causative conclusions is demonstrated. A proper evaluation of the role of investigation versus experimentation is cited in the work of W. G. Cochran as explicated by D. R. Rubin (1983). (TJH)

This overview of nonexperimental causal research methods focuses on latent variable structural equation modeling using the LISREL computer program. An extended example in special education is used to present LISREL as an extension of structural equations analysis (path analysis) and as a method of reducing the effects of error in research.…