Investigating Experimental Effects Within the Framework of Structural Equation Modeling: An Example With Effects on Both Error Scores and Reaction Times

Abstract

Structural equation modeling provides the framework for investigating experimental effects on the basis of variances and covariances in repeated measurements. A special type of confirmatory factor analysis as part of this framework enables the appropriate representation of the experimental effect and the separation of experimental and nonexperimental parts of variance. The constraint of the matrix of loadings is essential for the representation of the effect. Appropriate constraints of loadings are achievable with the aid of the polynomial function. The representation can even bear on several response modes. The usefulness of this method is demonstrated in data obtained by an experimental task with 3 treatment levels with respect to reaction times and error scores. A model with latent variables representing constancy and increase in reaction times and one latent variable representing increase in error scores serves best in these data. Both reaction times and error scores show experimental effects.

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