1. 用图表检验Analyze -> regression -> Linear-> Plots
# a, P8 K6 s. }0 ? h% nScatter plot of the standardised residuals on the standardised predicted values (ZRESID as the Y variable, and ZPRED as the X variable
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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。
4 g9 e1 h8 }4 S; A2. 用统计检验, I& o) k8 F0 z8 A( \
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 Test9 ?- m4 j; x/ [# A
Goldfeld-Quandt Test& l" W; f" M K0 C. n6 F. X
Breusch-Pagan Test% N% V- a$ @, @2 S
White‘s Test (比较常用来检验异方差)2 r. {: N$ P7 A( 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.
- K2 J/ @) r) p) i( x· Compare this value with c2 (n), i.e.with c2 (2016) . P1 C; k, Z% a) a: k
(c2 is the symbol for theChi-Square distribution)
h; N/ y1 R( e" hc2 (2016) = 124obtained from c2 table. (For 955 confidence) As n*R2 < c2 ,heteroskedasticity can not be confirmed.
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E: \; n+ p; P3 b" V( _ c请参考:regression_explained_SPSS
regression_explained_SPSS.doc
(368 KB, 下载次数: 0)
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