Abstract
This paper proposes a simple statistic for testing statistical significance of R squared. This statistic, called comparative R squared, also tests statistical significance of the difference of R squared between null and alternative models with additional explanatory variables. The asymptotic distribution of the test statistic is a chi square distribution with the degree of freedom equal to the number of (additional) explanatory variables. Unlike the F test, this statistic is useful when dealing with non-normality. Simulations show that the test statistic behaves well and has no distortion of size, even in small samples.
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