Scatter plot of the standardised residuals on the standardised predicted values (ZRESID as the Y variable, and ZPRED as the X variable
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。
2. 用统计检验
Heteroscedasticity——Testing and Correcting in SPSS.pdf
Levene’s Test
Goldfeld-Quandt Test
Breusch-Pagan Test
White‘s Test (比较常用来检验异方差)
Assume you want to run a regression of wage on age, work experience,education, gender, and a dummy for sectorof employment (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)
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