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

被引：16

作者：

Lorenzo-Seva, Urbano ^{[1
]}

Ferrando, Pere J. ^{[1
]}

机构：

[1] Univ Rovira & Virgili, Dept Psicol, Ctr Recerca Avalucio & Mesura Conducta, Tarragona 43007, Spain

来源：

BEHAVIOR RESEARCH METHODS | 2011年 / 43卷 / 01期

关键词：

Multiple linear regression; Variable selection; Relative importance; DUPLEX; SPSS; DOMINANCE ANALYSIS; NEGATIVE AFFECT; PANAS SCALES; VALIDATION; MODEL; WEIGHTS;

D O I：

10.3758/s13428-010-0043-y

中图分类号：

B841 [心理学研究方法];

学科分类号：

040201 ;

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.

引用

页码：1 / 7

页数：7

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