# PharmPK Discussion - Weighted calibration curves

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• On 25 Dec 2007 at 14:11:04, "Tahir Kasumov" (tmk2.aaa.case.edu) sent the message
`I would be very thankful if anyone could offer a step by step algoritmfor application of weightin procedure for calibration curves. It wouldbe very helpful, if one could define when wgeighting is legitimite andwhat type of wheighting coifficient need to be applied.Thank you.Sincerely, Tahir Kasumov, PhDCCF`
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• On 27 Dec 2007 at 08:06:16, "Vijay Bhaskar" (vijayb.-a-.aurigene.com) sent the message
`Dear Tahir Kasumov,                   As generally calibration curves are plotted using =20Least squares regression, Weighting minimizes the sum of squares of =20the relative distance of data from the curve. Generally 4 kinds of =20weightings will be used for Calibration curve (1/x, 1/x2, 1/y, and 1/=20y2). Selection of weighting factor solely depends upon the number of =20points that you select at LOQ/ULQ end. If the variation in dependent =20variable is more towards ULOQ end then you have to go for 1/y or 1/y2. =20=1/x or 1/x2 weighting will be selected when we want to weigh the =20points more towards left point of the graph i.e., at LOQ end.The formulas for calculating the weighting are1/x -> 1/xdata (xdata-xcurve)21/x2 -> 1/xdata2 (xdata-xcurve)2Similarly the same formulas are applicable to =93Y=94 weighting also. =More =20often =93y=94 weighting will be used and =93X=94 weighting will be used =rarely =20as there will be more necessity to weigh the points at the ULQ end due =20=to broader ranges (less no .of points at ULQ end).With Regards,Veeravalli Vijaya Bhaskar,Research Associate,Aurigene Discovery Technologies Limited,Bioanalytical Division,Bangalore,Email: vijayb.aaa.aurigene.com`
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• On 28 Dec 2007 at 00:16:11, "Akshanth Polepally" (akshanth.aaa.gmail.com) sent the message
`Dear Dr. Tahir Kasumov,I hope the following article will answer your query as I found it veryuseful in choosing a weghting factor for calibration curves.Almeida AM et al. "Linear regression for calibration lines revisited:weighting schemes for bioanalytical methods". J Chrom B. 774(2002):215 - 222.regardsAkshanth`
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• On 28 Dec 2007 at 16:28:05, "Ed O'Connor" (eoconnor.at.matrixbioanalytical.com) sent the message
`The following message was posted to: PharmPKBoth weightings will provide pretty much the same result. One usesweight based on the independent variable [conc, x], the other bases theweighting on the response (y).  Each will minimize the contribution ofhigh standards and maximize the contribution of the low standards to thecurve and curve fit.  Other types of weighting (log) will adjust for thehigh end of the curve and minimize the contribution of the low standardsThe selection should be driven by using the simplest model.  Linearunweighted > linear weighted, Linear > quadratic > 4PL.  The gauge tomeasure models is the % Bias for each of the points.--Ed O'Connor, Ph.D.Laboratory DirectorMatrix BioAnalytical Laboratories25 Science Park at YaleNew Haven, CT  06511Web:     www.matrixbioanalytical.comEmail:    eoconnor.-a-.matrixbioanalytical.com`
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