# How to interpret a predictor with a positive structure coefficient and a negative standardised coefficient in discriminant function analysis?

I am doing a discriminant function analysis and I have four continous independent variables and one categorical dependent variable (that has 3 groups). I have chosen to do this analysis to see how these groups can be predicted by the four independent variables.

• Firstly, when we are interpreting the results, do we look at standardised coefficients or the structure matrix coefficients? From my reading of the literature, I have found contradictory opinions. Some say that structure coefficients are better since they are more stable while others say that both standarized and structure coefficients should be looked at.

• Secondly, when I do look at both structure and standardized coefficients, two of my dependent variables have the opposite signs for their standardized and structure coefficients (for both of them the structure coefficient is positive and more than .30 whereas the standardized coefficient is negative and has a very small value). I have read up some stuff on it and I think these are suppressor variables (they are related to the other IV's but do not directly predict the DV). How are we supposed to handle these suppressor variables?

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• In particular, if you have two predictors that are correlated, whether it be multiple regression or discriminant function analysis, it is common for both predictors to predict the outcome on their own, but when combined, one of the variables appears to provide most of the prediction. This is possibly what is happening to you here. I wouldn't focus too much on the change in sign if, for example, the standardised coefficient is close to zero (e.g., perhaps $-.05$, or $-.10$).