Apologies in advance for my limited stats knowledge. I hope someone can help. I am trying to understand how to interpret the coefficients of both the linear and quadratic term in a binary logistic regression model.
When I fit the model, I get the following coefficients as:
x: 0.0265
x^2: -0.000462
Both coefficients are significant. I have other terms in my model, but I won't include them here. Taking the exponential of each coefficient, I get:
x: 1.0269
x^2: 0.9995
Now I understand if I had only the coefficient for x in my model, I would interpret this as the odds of a positive result in response variable y increasing by 2.69% for every 1 unit increase in x. But I'm not sure how to interpret the coefficient for the squared term. Is this saying that the increase in odds decreases by 0.05% for every 1 unit increase in x? i.e. the increase in odds is 2.69%, then 2.64%, then 2.59%, and so on, each time x increases by 1.
That is, the odds of a positive result in y are increasing as x increases but the rate of this growth is slowing down and eventually the odds will start to decrease? Or have I got this totally wrong?
Thanks in advance.