https://stats.stackexchange.com/a/373259/68357 is an example, I kust wonder if I have lm()...
Below is another example
>> x <- lm(mpg ~ cyl * disp * hp * drat, mtcars)
>> summary(x)
>
> Call:
> lm(formula = mpg ~ cyl * disp * hp * drat, data = mtcars)
>
> Residuals:
> Min 1Q Median 3Q Max
> -3.5725 -0.6603 0.0108 1.1017 2.6956
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 1.070e+03 3.856e+02 2.776 0.01350 *
> cyl -2.084e+02 7.196e+01 -2.896 0.01052 *
> disp -6.760e+00 3.700e+00 -1.827 0.08642 .
> hp -9.302e+00 3.295e+00 -2.823 0.01225 *
> drat -2.824e+02 1.073e+02 -2.633 0.01809 *
> cyl:disp 1.065e+00 5.034e-01 2.116 0.05038 .
> cyl:hp 1.587e+00 5.296e-01 2.996 0.00855 **
> disp:hp 7.422e-02 3.461e-02 2.145 0.04769 *
> cyl:drat 5.652e+01 2.036e+01 2.776 0.01350 *
> disp:drat 1.824e+00 1.011e+00 1.805 0.08990 .
> hp:drat 2.600e+00 9.226e-01 2.819 0.01236 *
> cyl:disp:hp -1.050e-02 4.518e-03 -2.323 0.03368 *
> cyl:disp:drat -2.884e-01 1.392e-01 -2.071 0.05484 .
> cyl:hp:drat -4.428e-01 1.504e-01 -2.945 0.00950 **
> disp:hp:drat -2.070e-02 9.568e-03 -2.163 0.04600 *
> cyl:disp:hp:drat 2.923e-03 1.254e-03 2.331 0.03317 *
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Residual standard error: 2.245 on 16 degrees of freedom
> Multiple R-squared: 0.9284, Adjusted R-squared: 0.8612
> F-statistic: 13.83 on 15 and 16 DF, p-value: 2.007e-06
Source : https://stat.ethz.ch/pipermail/r-help/2013-April/351761.html
mpg is y, may I know below calculation if correct?
-
cyl = cyl
-
disp = disp + cyl:disph + cyl:disp:hp + cyl:disp:drat + cyl:disp:hp:drat
-
hp = hp + cyl:hp + cyl:disp:hp +disp:hp:drat + cyl:disp:hp:drat
-
drat = drat + hp:drat + cyl:disp:drat + disp:hp:drat + cyl:disp:hp:drat