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Measuring Goodness of Fit for the Double‐Bounded Logit Model: Comment
Author(s) -
Harpman David A.,
Welsh Michael P.
Publication year - 1999
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1244463
Subject(s) - welsh , citation , logit , economics , library science , econometrics , computer science , philosophy , linguistics
Researchers estimating a regression model are often concerned about the joint significance of the explanatory variables and goodness of fit, among other factors. Goodness-of-fit measures and statistics for testing the joint significance of explanatory variables are closely related. For example, in ordinary least squares regression analysis both the goodness-of-fit measure, R2, and the F-statistic, which is used to test the joint significance of all coefficients except the constant, are based on the sum of squared residuals. Similarly, in maximum likelihood estimation both McFadden's R2 and