Testing model nesting and equivalence.
When using existing technology, it can be hard or impossible to determine whether two structural equation models that are being considered may be nested. There is also no routine technology for evaluating whether two very different structural models may be equivalent. A simple nesting and equivalence testing (NET) procedure is proposed that uses random sample and model-reproduced moment matrices to evaluate both model nesting and equivalence. The analysis is "local" rather than "global" in nature, but its use with simulation or bootstrapping can imply global conclusions. Two standard applications of NET are to verify whether or not two proposed models are equivalent and whether a baseline model used in an incremental fit index is appropriately nested.
Department of Psychology, University of California, Los Angeles, Box 951563, Los Angeles, CA 90095-1563, USA. bentler@ucla.edu
Peter M
PM
Bentler
Albert
A
Satorra
D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D006801:Humans; D008432:Mathematical Computing; D008960:Models, Psychological; D015233:Models, Statistical; D011584:Psychology / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data; D015203:Reproducibility of Results