How can adjusted r squared be negative?

Elliana Molina

Elliana Molina

Answered question

2022-11-02

How can adjusted r squared be negative?

Answer & Explanation

Raven Hawkins

Raven Hawkins

Beginner2022-11-03Added 19 answers

Step 1
R 2 , the coefficient of multiple determination, is defined as S S R E G S S T O T A L or,
equivalently, 1 - S S E S S T O . R 2 measures the proportionate reduction in variation of Y, associated with the set of X predictors. R 2 will be inflated as more X variables are added. The adjusted R 2 was therefore derived, as
R a d j 2 = 1 - { [ n - 1 n - p ] [ S S E S S T O ] }
If ( ) ,   n = 60 ,   p = 10.   so ,   n 1 n p = 59 50 = 1.18 , and you have R a d j 2 = 1 - ( 1.18 ) S S E S S T O . If the ratio S S E S S T O is close enough to 1, then you can see how the R a d j 2 . Can be negative. [In which case it can be interpreted as zero.]
[If negative] (...); you have too many predictors chasing too little information (a la small n). Just because one can run a model with n=60, and 10 predictors, does not mean that one should.

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