I had a question regarding the logistic regression function in R. I was wondering if there's a way to tell if predicted curves from a glm will be reasonably shaped or not, e.g. a nice S-shaped curve opposed to a flattened curve/straight line?
I'm not sure if there are any arguments or values that could analyze and provide information regarding this... I calculated the "boundary" using coefficients and it gives a single value, but even if the value is within acceptable range (for us, between 1-50), the curves sometimes come out to be flat/oddly shaped.
Previously, I've looked at AIC and residual values, but I was running into a similar issue where "reasonable" AIC and residual values generated oddly shaped/flat curves.
Standard code that is used to calculate logistic regression (run over multiple data points to estimate phonetic "boundaries"):
glm.1 <- glm(response~stimuli, family = binomial(link="logit") value <- -glm.1$coefficients/glm.1$coefficients
Logistic regression is a bit tricky for me to fully understand as I'm still learning about it, so I apologize for any confusion! Any help/suggestions are appreciated, thanks!