I have carried out an experiment with several repeats and my program has returned the values of EC50 and its CI(95%) confidence intervals, LogEC50 and the standard error of (LogEC50). The logs are from the Hill equation. The standard error in this case referring to curve fitting and not the SEM.
Following the Cochrane guidelines, I have calculated the SD's from the EC50 value and CI. https://handbook-5-1.cochrane.org/chapter_7/7_7_3_2_obtaining_standard_deviations_from_standard_errors_and.htm
I also have read on here (https://www.ncbi.nlm.nih.gov/books/NBK91994/) that a fitting error of an estimate (percentage wise) can be calculated from the the error of the LogEC50 by multiplying it by ln(10) * 100:
%FE(EC50)= FE(Log(EC50))*ln(10)*100
From which I assume you can infer the absolute fitting error by multiplying the EC50 by FE(Log(EC50))*ln(10).
The values I got seemed to closely allign with the SD's calculated earlier.
What I don't understand is what this formula actually does
I know Log10(EC50) can be rewritten as ln(EC50)/ln10 so I guess the ln(10)'s cancel out, but then what.
I understand that since the SE(Log(EC50)) is added and subtracted from the Log(EC50) it makes sense that we would be multiplying the absolute value by the error value (log(xy)=log(x)+log(y) and all that). I just can't seem to connect this intuition to whats actually happening in the formula provided
Thanks in advance