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--- multiple_regression_examples [2020/07/06 14:53] – [E.g. 1] hkimscil
+++ multiple_regression_examples [2020/07/06 15:04] – [E.g. 1] hkimscil
@@ Line 288: / Line 288: @@
 </code>
+이제 반대로 bmi 고유의 설명력을 보려면
+<code>
+lm.bmi.stress <- lm(bmi~stress)
+summary(lm.bmi.stress)
+anova(lm.bmi.stress)
+res.lm.bmi.stress <- lm.bmi.stress$residuals
+lm.happiness.reslmbmistress <- lm(happiness ~ res.lm.bmi.stress)
+summary(lm.happiness.reslmbmistress)
+anova(lm.happiness.reslmbmistress)
+</code>
+<code>
+> lm.bmi.stress <- lm(bmi~stress)
+> summary(lm.bmi.stress)
+Call:
+lm(formula = bmi ~ stress)
+Residuals:
+    Min      1Q  Median      3Q     Max
+-6.2169 -2.0524  0.3411  2.2700  5.2411
+Coefficients:
+            Estimate Std. Error t value Pr(>|t|)
+(Intercept)  11.8327     1.4152   8.361 4.27e-09 ***
+stress        4.7421     0.4536  10.454 3.58e-11 ***
+---
+Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+Residual standard error: 3.059 on 28 degrees of freedom
+Multiple R-squared:  0.796,	Adjusted R-squared:  0.7888
+F-statistic: 109.3 on 1 and 28 DF,  p-value: 3.58e-11
+> anova(lm.bmi.stress)
+Analysis of Variance Table
+Response: bmi
+          Df  Sum Sq Mean Sq F value   Pr(>F)
+stress     1 1022.42 1022.42  109.29 3.58e-11 ***
+Residuals 28  261.95    9.36
+---
+Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+> res.lm.bmi.stress <- lm.bmi.stress$residuals
+> lm.happiness.reslmbmistress <- lm(happiness ~ res.lm.bmi.stress)
+> summary(lm.happiness.reslmbmistress)
+Call:
+lm(formula = happiness ~ res.lm.bmi.stress)
+Residuals:
+     Min       1Q   Median       3Q      Max
+-1.97283 -0.94440  0.05897  0.97961  2.29664
+Coefficients:
+                  Estimate Std. Error t value Pr(>|t|)
+(Intercept)        2.83333    0.24698  11.472 4.27e-12 ***
+res.lm.bmi.stress -0.05954    0.08358  -0.712    0.482
+---
+Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+Residual standard error: 1.353 on 28 degrees of freedom
+Multiple R-squared:  0.0178,	Adjusted R-squared:  -0.01728
+F-statistic: 0.5074 on 1 and 28 DF,  p-value: 0.4822
+> anova(lm.happiness.reslmbmistress)
+Analysis of Variance Table
+Response: happiness
+                  Df Sum Sq Mean Sq F value Pr(>F)
+res.lm.bmi.stress  1  0.929 0.92851  0.5074 0.4822
+Residuals         28 51.238 1.82993
+</code>
+<code>
+Multiple R-squared:  0.0178,	Adjusted R-squared:  -0.01728
+F-statistic: 0.5074 on 1 and 28 DF,  p-value: 0.4822
+</code>
+stress: 8.1%
+bmi: 1.78%
+만이 독립변인의 고유영향력이고 이를 제외한
+.17 - (9.88) = 72.29 가
+공통영향력이라고 하겠다.