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...ity is the response variable and Correctness and Complexity are predictor variables. My current approach uses ordinal logistic regression with mixed effects. However, once a student ranks a single model, there is not an equal probability of each model being placed at any other rank. For example, if student_026 thinks Pink is the least correct and ranks it 1, then other models can only be placed in positions 2-9 (not all 9). This continues for each ranking. Ordinal regression assumes you have the same set of choices at every step. Has anyone encountered this situation when using ranked data as predicto...