FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors
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Published on: September 27, 2019
Urbano Lorenzo-Seva1, Pere J Ferrando
1Departament de Psicologia, Centre de Reçerca en Avalució i Mesura de la Conducta, Universitat Rovira i Virgili, Carretera Valls s/n, 43007 Tarragona, Spain. urbano.lorenzo@urv.cat
Abstract:
We provide an SPSS program that implements currently recommended techniques and recent developments for selecting variables in multiple linear regression analysis via the relative importance of predictors. The approach consists of: (1) optimally splitting the data for cross-validation, (2) selecting the final set of predictors to be retained in the equation regression, and (3) assessing the behavior of the chosen model using standard indices and procedures. The SPSS syntax, a short manual, and data files related to this article are available as supplemental materials from brm.psychonomic-journals.org/content/supplemental.
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