1. 用图表检验Analyze -> regression -> Linear-> Plots
* K5 O! H' Y+ T! G' l( |+ JScatter plot of the standardised residuals on the standardised predicted values (ZRESID as the Y variable, and ZPRED as the X variable7 a4 N- Z9 W& h, M
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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。
! E/ p" A+ B5 H; [; K2. 用统计检验 o3 z! W# O8 [
Heteroscedasticity——Testing and Correcting in SPSS.pdf
Gwilym Pryce March 2002.doc
(172.5 KB, 下载次数: 4)
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1 Q3 T: l# V. H/ \, f& ]Levene’s Test
/ [, G% b- _. g/ q5 [& yGoldfeld-Quandt Test
9 k( B* Z% l; a5 mBreusch-Pagan Test
/ a; m9 |3 w8 b3 cWhite‘s Test (比较常用来检验异方差)
# Y/ v" [/ p$ @# X7 p7 F* tAssume 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) ' E& W! X9 G0 S3 R7 M9 p5 R
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White’s Test · Calculate n*R2 à R2 = 0.037, n=2016 à Thus, n*R2 = .037*2016 = 74.6. h' e5 D! c0 e- m$ k
· Compare this value with c2 (n), i.e.with c2 (2016)
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1 d! a& W. U# t* S: lc2 (2016) = 124obtained from c2 table. (For 955 confidence) As n*R2 < c2 ,heteroskedasticity can not be confirmed.
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请参考:regression_explained_SPSS
regression_explained_SPSS.doc
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