Title: Comparing models using the extra sum-of squares F test
Abstract: Abstract When you compare two nested models, the model with more parameters will almost always fit the data better (have a lower sum-of-squares) than the model with fewer parameters. It is not enough to compare sum-of-squares. We need to use a statistical approach to decide which model to accept. As its name suggests, the extra sum-of-squares F test is based on the difference between the sum-of-squares of the two models. It also takes into account the number of data points and the number of parameters of each model. It uses this information to compute an F ratio, from which it calculates a P value.
Publication Year: 2004
Publication Date: 2004-05-27
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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