Unable to fit a 4PL curve after applying weighting (1/y^2)

[#1]

I am attempting to analyze a data set that utilizes raw signal points (y, response) and concentration (x, predictor formula) for an ELISA type assay using a logistic 4P model on the data. Once I apply a 1/y^2 weighting to the raw signal points column, the graph can no longer fit giving an R = ~0.45. This same plate has been analyzed with another software okay, so I am wondering what is happening here. Any help is appreciated! 

weighting calculation: 

[#2]

It's difficult to discern what the issue is without data, could you provide the example of what you're discussing?

Thanks,
Ben

[#3]

Hi Ben, 

I appreciate your response! Below are the numbers I am working with. It's a simple dilution series that I am trying to get to fit with the "ave signal col 1 and 2" on my Y axis and "Theoretical Concentration" as my X. The weighting column is from using the above formulation in the original post. After analyzing with a non-linear model, the 4PL doesnt fit (it does when weighting is removed) 

[#4]

Hi @CurseOfCheetah8 ,

The L4P seems to be working as intended with the weighting, it is just struggling because the weighted data is a poor fit for a 4 parameter model, which you can see in the parameter estimates table:

It might be that the equation in your software is different to the one JMP uses? If so you could try and bring that over and use the Non-linear platform.

Let me know if there are differences and I can send some more resources to help.

Thanks,

Ben

[#5]

Is it reasonable to model this data with any 4PLC when the response is essentially linear to the change in concentration?