Hello,
I am trying to model the data for each treatment separately, for x and y to predict the value corresponding to x of y/100 = 0,5 and the inflection point of the generated logistic curve. I want a logistic model with 2P because assyp. is known (1).
To do this, on the recommendation of a staff member (thank you very much) I am trying two different ways: using GLMM in Fit Model and the non-linear platform.
Starting with the problem I am having in GLMM, I have several questions about it:
1. How can I know the inflection point of that curve? I didn't find a menu option to show it.
2. The error std. Using the binomial distribution (I have searched about it, and for proportions I think it is the best choice, but I am not sure) the error is so high in treatment C (one of the initial problems), but also in treatment A (I did not have this problem before). Is the distribution I have chosen the main problem?
3. Finally, using the binomial distribution, in many treatments the probability Chisqr is not significant for the “model”, but the goodness-of-fit statistics have a good value (I found it in a JMP answer in a community post). With this value of Chisqr, does the model have a good result?
Regarding the way of modeling with the non-linear platform, as you can see in the scripts, I have tried equations with different parametrization (and Log2P from JMP) but I have a problem when I press 'Go'. The result doesn't fit the curve I want, and I think it may be caused by the initial values of the parameters. Is there any form to estimate this initial value to avoid this error? Also, when I try to make a custom inverse prediction it fails.
I attach in this post an anonymous dataset of the values. The objective is to obtain good result for that what I have tried in the scripts, despite of the data limitations.
Thank you in advance.