I am trying to get to the bottom of an odd observation when trying to fit data using a 4PL. In short, when I fit my data I end up with a flat line:
![P_Desmond_0-1614295895731.png P_Desmond_0-1614295895731.png](https://community.jmp.com/t5/image/serverpage/image-id/30720iCEFEA486962C13A1/image-dimensions/234x286?v=v2)
![P_Desmond_1-1614295924067.png P_Desmond_1-1614295924067.png](https://community.jmp.com/t5/image/serverpage/image-id/30721iAE2292D95048015C/image-dimensions/169x161?v=v2)
If I do any of the following I end up with a more proper looking fit, and I am sure that other minor changes to the numbers themselves may also fix this bug:
- Change 0.08 to 0.0800000001
- Change 26042 to 26043
- Invert the way the data is within the table (weirdest one to me because it is the same exact numbers)
Here is the resulting fit:
![P_Desmond_2-1614296196537.png P_Desmond_2-1614296196537.png](https://community.jmp.com/t5/image/serverpage/image-id/30722i293BED40DEBF2031/image-size/medium?v=v2&px=400)
![P_Desmond_3-1614296202808.png P_Desmond_3-1614296202808.png](https://community.jmp.com/t5/image/serverpage/image-id/30723i5DFCAB2B0D8B2DA2/image-dimensions/219x237?v=v2)
Regardless of whether this is the correct fit to use for this data set, it is strange to see this odd behavior. If there is another explanation other than a bug/glitch and someone can explain that would be amazing!