On the Merits of Orthogonalizing Powered and Product Terms: Implications for Modeling Interactions Among Latent Variables

University of Kansas · University of California, Davis

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Abstract

Abstract The goals of this article are twofold: (a) briefly highlight the merits of residual centering for representing interaction and powered terms in standard regression contexts (e.g., Lance, 1988), and (b) extend the residual centering procedure to represent latent variable interactions. The proposed method for representing latent variable interactions has potential advantages over extant procedures. First, the latent variable interaction is derived from the observed covariation pattern among all possible indicators of the interaction. Second, no constraints on particular estimated parameters need to be placed. Third, no recalculations of parameters are required. Fourth, model estimates are stable and…

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Topics & keywords

Keywords
  • Collinearity
  • Latent variable
  • Residual
  • Latent variable model
  • Variable (mathematics)
  • Structural equation modeling
  • Computer science
  • Interpretation (philosophy)
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