FIRE: an SPSS program for variable selection in multiple linear regression analysis via the relative importance of predictors

被引：0
|
作者：
Urbano Lorenzo-Seva
Pere J. Ferrando
机构：
[1] Universitat Rovira i Virgili,Departament de Psicologia, Centre de Reçerca en Avalució i Mesura de la Conducta
来源：
Behavior Research Methods | 2011年 / 43卷
关键词：
Multiple linear regression; Variable selection; Relative importance; DUPLEX; SPSS;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：1 / 7
页数：6
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