User Tools

Site Tools


multiple_regression

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revisionBoth sides next revision
multiple_regression [2019/05/21 22:33] – [무엇부터? 라는 문제] hkimscilmultiple_regression [2019/05/21 22:40] – [Why overall model is significant while IVs are not?] hkimscil
Line 331: Line 331:
 see https://www.researchgate.net/post/Why_is_the_Multiple_regression_model_not_significant_while_simple_regression_for_the_same_variables_is_significant see https://www.researchgate.net/post/Why_is_the_Multiple_regression_model_not_significant_while_simple_regression_for_the_same_variables_is_significant
  
-This problem +<code>> RSS = 3:10 #Right shoe size 
 +> LSS = rnorm(RSS, RSS, 0.1) #Left shoe size - similar to RSS 
 +> cor(LSS, RSS) #correlation ~ 0.99 
 +[1] 0.9983294 
 +>  
 +> weights = 120 + rnorm(RSS, 10*RSS, 10) 
 +>  
 +> ##Fit a joint model 
 +> m = lm(weights ~ LSS + RSS) 
 +>  
 +> ##F-value is very small, but neither LSS or RSS are significant 
 +> summary(m) 
 + 
 +Call: 
 +lm(formula = weights ~ LSS + RSS) 
 + 
 +Residuals: 
 +      1                                     7  
 + 4.6231 -4.8706  1.3063  0.9639 -1.3120 -6.1247  2.6604  
 +      8  
 + 2.7536  
 + 
 +Coefficients: 
 +            Estimate Std. Error t value Pr(>|t|)     
 +(Intercept)  103.116      4.832  21.339 4.19e-06 *** 
 +LSS          -27.546     11.952  -2.305   0.0694 .   
 +RSS           39.299     12.040   3.264   0.0223 *   
 +--- 
 +Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
 + 
 +Residual standard error: 4.508 on 5 degrees of freedom 
 +Multiple R-squared:  0.9827, Adjusted R-squared:  0.9757  
 +F-statistic: 141.6 on 2 and 5 DF,  p-value: 3.964e-05 
 + 
 +>  
 +> ##Fitting RSS or LSS separately gives a significant result.  
 +> summary(lm(weights ~ LSS)) 
 + 
 +Call: 
 +lm(formula = weights ~ LSS) 
 + 
 +Residuals: 
 +    Min      1Q  Median      3Q     Max  
 +-11.044  -2.203  -0.422   2.774  12.369  
 + 
 +Coefficients: 
 +            Estimate Std. Error t value Pr(>|t|)     
 +(Intercept)  105.939      7.679   13.79 9.03e-06 *** 
 +LSS           11.401      1.115   10.22 5.11e-05 *** 
 +--- 
 +Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
 + 
 +Residual standard error: 7.282 on 6 degrees of freedom 
 +Multiple R-squared:  0.9457, Adjusted R-squared:  0.9366  
 +F-statistic: 104.5 on 1 and 6 DF,  p-value: 5.113e-05 
 + 
 +>  
 +</code>
  
  
multiple_regression.txt · Last modified: 2023/10/19 08:39 by hkimscil

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki