I have an ordinal mixed model with four multilevel predictors (it's for exploration). My response variable is ranking 1-4 and so is one of my predictors. My question is if I should treat this ordinal predictor as a continuous variable or a multilevel categorical?
Just some background, in the experiment children selected who they would most like to play with from four photos. The first photo that was selected was given rank 1, the second photo rank 2, third photo rank 3 and the last photo a rank of 4. This is my response variable and the predictor I'm unsure about has exactly the same format but for 'who is most like you?'
I've read loads but almost all I can find is how to treat Likert-scale data and I feel like mine isn't quite that. As far as I can tell I either treat it as a continuous (not do any manipulation) or I recode it into three variables where each ranking is compared to rank 1 ("the best"). Does anyone know for sure?