1. 用图表检验Analyze -> regression -> Linear-> Plots- P5 M( [1 z* Q4 T
Scatter plot of the standardised residuals on the standardised predicted values (ZRESID as the Y variable, and ZPRED as the X variable' ]7 H Y$ f& f* k5 T9 ?
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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。
/ _; E1 K& [' Z0 ^2 x2. 用统计检验
5 u2 [* Z3 ^+ t" G/ b; FHeteroscedasticity——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 Test
" U. U* V" T6 c+ Y5 @Goldfeld-Quandt Test
; b" H. _% Z4 j- B3 o1 t ~) gBreusch-Pagan Test
, x$ [- h3 d# m* B1 |7 kWhite‘s Test (比较常用来检验异方差)
% P, f- |1 M/ nAssume 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) + l+ L2 o, E' K
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White’s Test · Calculate n*R2 à R2 = 0.037, n=2016 à Thus, n*R2 = .037*2016 = 74.6. 7 D4 o9 r a& Z
· Compare this value with c2 (n), i.e.with c2 (2016)
# @& E1 g/ Y- u; N& e* s(c2 is the symbol for theChi-Square distribution)
0 ]4 J5 m, j# E ? Tc2 (2016) = 124obtained from c2 table. (For 955 confidence) As n*R2 < c2 ,heteroskedasticity can not be confirmed. # g. ^ ~+ w$ f7 c
Y. V, i3 F9 m6 v请参考:regression_explained_SPSS
regression_explained_SPSS.doc
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