How interpret contrary coefficient estimates in a logistic regression?
I need help to interpret a result output of a mediation analysis.
I have a predictor X that predicts three mediators variables M1, M2, M3 in a negative way. When X increases M1, M2, M3 decreases. M1, M2, M3 predicts a binary response outcome Y, but M1 and M3 in a positive way, while M3 in a negative way.
I am having some difficulty interpreting the result where the relationships between X and M are parallel, but the effects of M on Y are contrary across M variables. Could you help me?
Comments
I think you would need to be more explicit about what these variables mean, and what the results show...based on your description it does seem like a puzzle. Perhaps it is best to do some checks...if you are missing some key variables you can get strange results in these kinds of models.
EJ