| 1. | Often the response variable may not be continuous but rather discrete.
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| 2. | One complication is how to best deal with the response variable.
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| 3. | However, these assumptions are inappropriate for some types of response variables.
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| 4. | Measurements of patient deaths and harm are often used as response variables.
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| 5. | Is the " i " th predicted value of the response variable.
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| 6. | The form of the distribution assumed for the response variable y, is very general.
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| 7. | Such implementations also allow use of truncated distributions and censored ( or interval ) response variables.
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| 8. | However, it is not equivariant under affine transformations of both the predictor and response variables.
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| 9. | This requirement then implies that one must first specify the distribution of the response variables observed.
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| 10. | The logarithm of the expected value of the response variable is a linear combination of the explanatory variables.
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