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既然s,d已经进行了标准化,其他变量是否进行标准化不会改变标准化了的s,d的系数
见下面栗子
sysuse auto,clear
egen std_weight=std(weight)
egen std_mpg=std(mpg)
egen std_length=std(length)
regress price weight mpg length foreign
regress price std_weight std_mpg length foreign
Source SS df MS Number of obs = 74
F( 4, 69) = 21.01
Model 348708940 4 87177235.1 Prob > F = 0.0000
Residual 286356456 69 4150093.56 R-squared = 0.5491
Adj R-squared = 0.5230
Total 635065396 73 8699525.97 Root MSE = 2037.2
price Coef. Std. Err. t P>t [95% Conf. Interval]
std_weight 4442.579 789.7025 5.63 0.000 2867.166 6017.993
std_mpg -77.56735 417.1788 -0.19 0.853 -909.8163 754.6816
length -92.48019 33.5912 -2.75 0.008 -159.4928 -25.46758
foreign 3550.194 655.4564 5.42 0.000 2242.594 4857.793
_cons 22489.82 6333.559 3.55 0.001 9854.716 35124.92
regress price std_weight std_mpg std_length foreign
Source SS df MS Number of obs = 74
F( 4, 69) = 21.01
Model 348708941 4 87177235.3 Prob > F = 0.0000
Residual 286356455 69 4150093.55 R-squared = 0.5491
Adj R-squared = 0.5230
Total 635065396 73 8699525.97 Root MSE = 2037.2
price Coef. Std. Err. t P>t [95% Conf. Interval]
std_weight 4442.579 789.7025 5.63 0.000 2867.166 6017.993
std_mpg -77.56736 417.1788 -0.19 0.853 -909.8163 754.6816
std_length -2059.195 747.953 -2.75 0.008 -3551.321 -567.0699
foreign 3550.194 655.4564 5.42 0.000 2242.594 4857.793
_cons 5109.794 306.6837 16.66 0.000 4497.977 5721.611
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