| 21. | The primary differences involve the assumptions required about the explanatory variables and the ability to model continuous versus binary outcomes.
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| 22. | In the process, the model attempts to explain the relative effect of differing explanatory variables on the different outcomes.
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| 23. | Dummy variables are incorporated in the same way as quantitative variables are included ( as explanatory variables ) in regression models.
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| 24. | For instance, when lagged dependent variables are included in the explanatory variables, then it is inappropriate to use this test.
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| 25. | In regression problems, the explanatory variables are often fixed, or at least observed with more control than the response variable.
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| 26. | Finally " r " is the number of modelled smoothed non-parametric functions to be used as constructed explanatory variables.
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| 27. | Both situations produce the same value for " Y " " i " * regardless of settings of explanatory variables.
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| 28. | Further, the Langmann study analyzed more explanatory variables than the Tristan study, which only looked at the effects of age and alcohol use.
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| 29. | Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or " features ".
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| 30. | The model assumes that, for a binary outcome ( Bernoulli trial ), Y, and its associated vector of explanatory variables, X,
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