利用spss进行异方差检验的方法，望借鉴

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1. 用图表检验Analyze -> regression -> Linear-> Plots
/ C( h0 l5 g# y1 yScatter 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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1 M5 X5 u; E, l8 H: ?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。
- I8 u9 J8 L9 w; e- K% x* ~) W2. 用统计检验
9 a) c$ O+ E$ R3 g; XHeteroscedasticity——Testing and Correcting in SPSS.pdf Gwilym Pryce March 2002.doc (172.5 KB, 下载次数: 4)

2013-10-13 16:09 上传

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Levene’s Test
! V* D" S! W: E8 qGoldfeld-Quandt Test
Breusch-Pagan Test
: k2 X: U- o6 ?. H1 _9 M1 |2 K% CWhite‘s Test （比较常用来检验异方差）
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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.

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·        Compare this value with c2 (n), i.e.with  c2 (2016)  
(c2  is the symbol for theChi-Square distribution)

c2 (2016) = 124obtained from c2 table.            (For 955 confidence)              As n*R2  < c2 ,heteroskedasticity can not be confirmed.

, p$ Z0 g! ?) C请参考：regression_explained_SPSS regression_explained_SPSS.doc (368 KB, 下载次数: 0)

2013-10-13 16:12 上传

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