I'm analysing the results of an election with 42 candidates, and wish to test for a relationship between the order presented on the ballot and the number of votes each candidate received.
So far I've just used a simple bivariate model. Candidate ballot position (1st to 42nd) is the independent variable and number of votes as a dependent variable. Is it acceptable to use an ordinal as the independent variable in this way?
Of course neither variable is normally distributed. For the original data p= 0.0043 If I change this to a Box Cox distribution p=0.0034.
Is there a better approach?
So far I've just used a simple bivariate model. Candidate ballot position (1st to 42nd) is the independent variable and number of votes as a dependent variable. Is it acceptable to use an ordinal as the independent variable in this way?
Of course neither variable is normally distributed. For the original data p= 0.0043 If I change this to a Box Cox distribution p=0.0034.
Is there a better approach?