1. 用图表检验Analyze -> regression -> Linear-> Plots; h8 l( T1 ]0 w( A* B
Scatter plot of the standardised residuals on the standardised predicted values (ZRESID as the Y variable, and ZPRED as the X variable- [5 {% u6 \. B$ g$ y- U, ]
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如果图表显示有可能存在异方差,需要用统计检验来进一步检测异方差是否确实存在。
. y. B/ o8 I( p4 m2 R" X5 [' A* G2. 用统计检验. o' W, ]2 k0 |7 [4 r: M
Heteroscedasticity——Testing and Correcting in SPSS.pdf
Gwilym Pryce March 2002.doc
(172.5 KB, 下载次数: 4)
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Levene’s Test/ k" }, f) K8 d6 a: s0 s3 ~% U
Goldfeld-Quandt Test
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White‘s Test (比较常用来检验异方差)+ I) c! D6 A+ e, y3 X, F: Q2 t' N
Assume you want to run a regression of wage on age, work experience,education, gender, and a dummy for sectorofemployment (whether employed in the public sector). wage = function(age, workexperience, education, gender, sector) or, as your textbook will have it, wage = b1 + b2*age + b3*work experience+ b4*education + b5*gender + b6*sector The White’s test is usually used as a test for heteroskedasticity. In this test, a regression of the squares ofthe residuals is run on the variables suspected of causing theheteroskedasticity, their squares, and cross products. (residuals)2 = b0 + b1 educ + b2 work_ex+ b3 (educ)2 + b4 (work_ex)2 + b5(educ*work_ex)
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White’s Test · Calculate n*R2 à R2 = 0.037, n=2016 à Thus, n*R2 = .037*2016 = 74.6. . W$ P. k6 w' g D+ |' ^
· Compare this value with c2 (n), i.e.with c2 (2016) ( q! ^. r9 u: r2 {+ z' y# W7 F
(c2 is the symbol for theChi-Square distribution) d5 B. X/ n+ o9 M
c2 (2016) = 124obtained from c2 table. (For 955 confidence) As n*R2 < c2 ,heteroskedasticity can not be confirmed. 3 y8 F9 _' u' ?- r
. q7 m, V' h( M0 _) U! N g7 T请参考:regression_explained_SPSS
regression_explained_SPSS.doc
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