title: FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors.
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.
authors.affiliation: Departament 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
authors.forename: Urbano
authors.initials: U
authors.lastname: Lorenzo-Seva
authors.forename: Pere J
authors.initials: PJ
authors.lastname: Ferrando
mesh_terms: D001519:Behavior; D001525:Behavioral Sciences / Q000706:statistics & numerical data*; D005544:Forecasting / Q000379:methods*; D006801:Humans; D016014:Linear Models; D010556:Personality Tests; D012015:Reference Standards; D012984:Software; D055815:Young Adult