%Gra: an SAS macro for generalized redundancy analysis

ABSTRACT

In the framework of redundancy analysis and reduced rank regression, the extended redundancy analysis model managed to account for more than two blocks of manifest variables in its specification. A further extension, the generalized redundancy analysis (GRA), has been recently proposed in literature, with the aim of incorporating external covariates into the model, thanks to a new estimation algorithm that manages to separate all the contributions of the exogenous and external covariates in the formation of the latent composites. At present, software to estimate GRA models is not available. In this paper, we provide an SAS macro, %GRA, to specify and fit structural relationships, with an application to illustrate the use of the macro.

KEYWORDS:

• Redundancy analysis
• SAS macro
• alternating least squares
• latent components
• reduced rank regression

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Pietro Giorgio Lovaglio http://orcid.org/0000-0002-2340-0547

Gianmarco Vacca http://orcid.org/0000-0002-8996-5524