Analyzing Max-Diff Using Standard Logit Models
The Multinomial Logit Model and its various mixture generalizations are designed to predict a choice from amongst a set of alternatives. These models can be 'tricked' to analyze max-diff data by treating each set (i.e., block) in the Max-Diff experiment as two separate sets. In the first set the dependent variable is the Best choice. In the second set, the Worst choice is the dependent variable and the independent variables are multiplied by -1. Worked examples are presented in:
- Max-Diff Analysis
- Counts Analysis of Max-Diff Data.
- Analyzing Max-Diff Using the Rank-Ordered Logit Models With Ties.
- Max-Diff Analysis Case Study Using R.
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