A tetrad test for causal indicators.
The authors propose a confirmatory tetrad analysis test to distinguish causal from effect indicators in structural equation models. The test uses "nested" vanishing tetrads that are often implied when comparing causal and effect indicator models. The authors present typical models that researchers can use to determine the vanishing tetrads for 4 or more variables. They also provide the vanishing tetrads for mixtures of causal and effect indicators, for models with fewer than 4 indicators per latent variable, or for cases with correlated errors. The authors illustrate the test results for several simulation and empirical examples and emphasize that their technique is a theory-testing rather than a model-generating approach. They also review limitations of the procedure including the indistinguishable tetrad equivalent models, the largely unknown finite sample behavior of the test statistic, and the inability of any procedure to fully validate a model specification.
Department of Sociology, University of North Carolina at Chapel Hill 27599-3210, USA. bollen@unc.edu
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D015984:Causality; D006801:Humans; D015233:Models, Statistical; D011594:Psychometrics; D012942:Social Sciences / Q000706:statistics & numerical data