I conducted an experiment and would like to know if how I treated and coded my treatment variable is permissible. Basically, participants rated targets that vary in terms of how similar they are to each participant. I have 6 levels of SIMILARITY (the treatment variable), going from low to high (an ordinal variable). Our analyses indicate SIMILARITY is almost perfectly step-wise so I am treating SIMILARITY as if continuous in regression analyses to avoid having 5 dummy (or effects coded) variables.
I have coded SIMILARITY as 0, 1, 2, 3, 4, 5, so that zero (and intercept) are meaningful (zero capturing lowest level of SIMILARITY). Doing this allows me to make a statement about other predictors in the regression model for targets that are low in similarity. And then I recode SIMILARITY, for example, by shifting the zero (e.g., -1, 0, 1, 2, 3, 4) so that my intercept and other predictors could be interpreted for the second lowest level of similarity (ordinally, this would be level 2, going from low to high).
Is treating similarity this way (shifting the zero across iterations of the model) problematic? I am conducting multilevel models because my design is repeated measure experimental design, but I am not sure that info is necessary to my inquiry.
Thank you for any thoughts on the matter! Dita