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 revision
Previous revision
Next revisionBoth sides next revision
multiple_regression [2019/05/21 21:37] – [e.g.] hkimscilmultiple_regression [2019/05/21 22:40] – [Why overall model is significant while IVs are not?] hkimscil
Line 328: Line 328:
 </code> </code>
  
-====== 무엇부터라는 문제 ======+====== Why overall model is significant while IVs are not====== 
 +see https://www.researchgate.net/post/Why_is_the_Multiple_regression_model_not_significant_while_simple_regression_for_the_same_variables_is_significant 
 + 
 +<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> 
 + 
 + 
 +====== The problem of "which one is entered first?" ======
  
 __그림 여기쯤 수록__ __그림 여기쯤 수록__
multiple_regression.txt · Last modified: 2023/10/19 08:39 by hkimscil

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki