Bit of background info on the data and methods that I've used. I have a forest road data that consists of one dependent variable which has 4 classes (0-3). The Dependent variable reflects possibility to use heavy log trucks on the road during different seasons: 0 = whole year around, 1 = summer and winter, 2 = dry summer and winter, 3 = only winter(frozen ground). In addition I have independent variables that reflect the condition of the road and thus affect the trafficability of the road during different seasons. Independent variables are such as: width of the road, wetness index, soil that the road has been built on, etc. As a whole there are seven independent variables. I have normalized the independent variables (even though it is not necessary in MLR) to range between 0 and 1 according to the goodness of the variable, for example soil: 0.1 gravel, 0.3 sand, 0.5 sandy moraine, 0.8 peat, 1 high amount of clay.
Now for the real question. I have run the multinomial logistic regression in SPSS and R. Both of these give me the Coefficients of the regression functions which is fine but the coefficients are only for three (1-3) functions for predicting the trafficability class which there are in total four (0-3). I understand that in this case the trafficability class zero is the 'reference category'. How do I get the coefficients to the function of the reference category OR how can I decide wether a case belongs to the reference category (0) or to some other category (1-3). Coefficients and std. Errors from R's MLR
Or do you have some other methods I could use beside from MLR. I think normal regression in this case is acceptable because independent variables have been changed to continuous values from categorical values. In that case it doesn't matter if result is a continuous value and not categorical.
Any tips would be hugely appreciated. Thank you