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
1 n: i& b: t" m% u- DScatter plot of the standardised residuals on the standardised predicted values (ZRESID as  the Y variable, and ZPRED as the X variable

+ J% X. {3 t% s6 [$ O# u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。
: A% B' `  B1 t( V! m/ g2 F2. 用统计检验
0 ?! E2 s% O! Q3 ~8 I: n1 U2 O( sHeteroscedasticity——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
4 _  n- k5 C- b1 W/ RGoldfeld-Quandt Test
Breusch-Pagan Test
6 ?! N- h" C, R" |3 f& w( yWhite‘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.

·        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.

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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