how to calculate relative potency in parallel line model?

[#1]

Hi,

I fitted the parallel line model LogY=Sample+Log_Dose in fit curve. 

The parallelism test and model parameters are fine. They are exactly same as what I got in R or PLA software.  But the relative potencies are totally different. Any place to find the technical details about its calculation? Thank you! 

[#2]

A small test data table, the different codes used and an overview of the results will facilitate the investigation.

[#3]

I used the example from PLA. The RP from R is 2.170981, which is the same as what I got from PLA software. But JMP's result is 5.9..

The estimated parameters are the same, so I think both are using the same model, just the RP from JMP is too large.

data <- read_excel("PLA Example_parallel line.xlsx", sheet = "Sheet1")
data$Log_Dose = log(data$Dose)
data$LogY = log(data$Y)

fit <- lm(LogY ~ Sample+Log_Dose , data = data) #parallel line model: common slope
summary(fit)
coefficients <- coef(fit)
db <- coefficients["SampleT"] #
beta <- coefficients["Log_Dose"]
LogRP <- db / beta
RP<-exp(logRP)

In JMP, I fitted the model in specialized modeling-> fit curve, polynomials->Fit linear, and test parallelism 

[#4]

Predictive and Specialized Modeling > Fit Curve > Model Fit Options > Test Parallelism does contain some information