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Logistic Regression Using SAS®: Theory and Application by Paul D. Allison

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7.3. Model and Estimation

Now that we’ve seen how to do a discrete choice analysis, let’s look more closely at the model being estimated. Suppose we have i=1, ...,n individuals and each individual is presented with j=1, ...,Ji options. We write the number of possible choices as Ji to indicate that different individuals may have different sets of options. That wasn’t true for the chocolate example, but it’s an important feature of the model that distinguishes it from the multinomial logit model of Chapter 5. Let yij = 1 if individual i chooses option j, otherwise 0, and let xij be a vector of explanatory variables describing option j for person i. This set of explanatory variables may include dummy variables for the various options and interactions ...

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