1. 用图表检验Analyze -> regression -> Linear-> Plots6 n3 j1 Q: _6 v
Scatter 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。3 r; b( K7 _0 \# o( |# P0 Y
2. 用统计检验
3 Q5 s+ R3 u0 j C2 y4 Q! c" D I, pHeteroscedasticity——Testing and Correcting in SPSS.pdf
Gwilym Pryce March 2002.doc
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" r, D6 f( m+ g0 z2 f( }Levene’s Test; r+ c) q9 Y% }' r4 t4 v
Goldfeld-Quandt Test7 ?* a( H- y n
Breusch-Pagan Test" X# \) R) ?6 N" p& q! E
White‘s Test (比较常用来检验异方差)6 m/ c/ \3 O k1 X7 g2 p1 x
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. ' R1 k1 I" l$ b/ W! a3 |$ a6 b
· Compare this value with c2 (n), i.e.with c2 (2016)
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( b( ?7 N, m% y( j% \c2 (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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