Abstract
Sample coefficient of determination and its adjusted version are two popular measures for the goodness of fit in linear regression models. Their performance properties under the criteria of Pitman nearness and concentration probability are analyzed using large sample approximations and are compared with those under the criteria of bias and mean squared error.
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