I have a dataset that I am trying to analyse, it consists of:
- A binary variable which indicates a tree species (0 = deciduous 1 = evergreen) with 100 measurements each.
- N which is leaf nitrogen content (%, continuous)
- P - leaf phosphorus content (%, continuous)
- SLA - specific leaf area measurements (cm2, g-1, continuous)
- Lignin content (%, continuous)
I am trying to test to see which traits differentiate between the two tree types. I initially analysed this using a logistic regression using glm() in R but now I am not sure if this is the correct analysis. When I used the exp() function to convert the coefficients, it produced these values from the output:
(Intercept) - 2.235862e-06
sq_sla - 3.585946e+00
l_p - 5.352951e-03
N - 3.920587e-01
It seems like there is something wrong but I have done all of the procedures correctly for the model so I am wondering if the test is appropriate.