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Pohlmann, John T. – Mid-Western Educational Researcher, 1993
Nonlinear relationships and latent variable assumptions can lead to serious specification errors in structural models. A quadratic relationship, described by a linear structural model with a latent variable, is shown to have less predictive validity than a simple manifest variable regression model. Advocates the use of simpler preliminary…
Descriptors: Causal Models, Error of Measurement, Predictor Variables, Research Methodology

Schumacker, Randall E. – Mid-Western Educational Researcher, 1993
Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)
Descriptors: Causal Models, Data Analysis, Error of Measurement, Factor Analysis

Sheehan, Janet K.; Han, Tianqi – Mid-Western Educational Researcher, 1996
Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…
Descriptors: Aptitude Treatment Interaction, Causal Models, Context Effect, Educational Research