Principal component regression analysis with SPSS

被引：231
|
作者：
Liu, RX [1 ]
Kuang, J
Gong, Q
Hou, XL
机构：
[1] Jinan Univ, Coll Med, Guangzhou 510362, Peoples R China
[2] Guangdong Prov Peoples Hosp, Guangzhou 510080, Peoples R China
[3] Jinan Univ Lib, Guangzhou 510632, Peoples R China
来源：
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2003年 / 71卷 / 02期
关键词：
multicollinearity diagnosis; principal component regression analysis; SPSS;
D O I：
10.1016/S0169-2607(02)00058-5
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with spss 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correclations procedures in spss 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with spss. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.
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页码：141 / 147
页数：7
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