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It is common to assess the performance of linear probability and logistic regression models on the basis of the '________________________' rates defined as the percentage of correctly classified observations
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- A measure of the extent to which two factors vary together, and thus of how well either factor predicts the other.
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- For 0 < β1 < 1, the log-log regression model implies a positive relationship between x and E(y); as x increases, E(y) increases at a slower rate. This may be appropriate in the food expenditure example where we expect food expenditure to react positively to changes in income, with the impact diminishing at higher income levels. If β1 < 0, what is the relationship between x and E(y)?As x increases, E(y) decreases at a faster rateAs x increases, E(y) decreases at a slower rateAs x increases, E(y) increases at a slower rateImplies a positive and increasing relationship between x and y