Ram B Jain1. 1. Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Chamblee, GA 30341, USA. RIJ0@cdc.gov
Abstract
BACKGROUND: To minimize the effect of heteroscedasticity in chemical and other data, weighted regression analysis is the preferred regression technique. In this work a regression weight that maximizes accuracy and precision was sought. METHOD: Using real and simulated data from a serum cotinine assay, performance of 3 weighting schemes, namely, 1/X, 1/X(2), and 1/s(2)(Y) to calibrate chemical data was evaluated. Two performance measures were used to evaluate the accuracy and precision of each scheme to estimate concentrations in unknown specimens. RESULTS: The weight, 1/X-particularly for low concentrations-was not acceptable. The performance of both, 1/X(2) and 1/s(2)(Y) was close, 1/X(2) being slightly better in many cases. Overall, however, when the variance of instrument signal increased beyond certain limits, none of the weighting schemes performed acceptably. CONCLUSION: Because of its simplicity and ease of use, 1/X(2) is recommended for general application. If, however, instrument signal variance is too high to be managed by statistical techniques, the only solution is to control such variance through laboratory-based solutions. Published by Elsevier B.V.
BACKGROUND: To minimize the effect of heteroscedasticity in chemical and other data, weighted regression analysis is the preferred regression technique. In this work a regression weight that maximizes accuracy and precision was sought. METHOD: Using real and simulated data from a serum cotinine assay, performance of 3 weighting schemes, namely, 1/X, 1/X(2), and 1/s(2)(Y) to calibrate chemical data was evaluated. Two performance measures were used to evaluate the accuracy and precision of each scheme to estimate concentrations in unknown specimens. RESULTS: The weight, 1/X-particularly for low concentrations-was not acceptable. The performance of both, 1/X(2) and 1/s(2)(Y) was close, 1/X(2) being slightly better in many cases. Overall, however, when the variance of instrument signal increased beyond certain limits, none of the weighting schemes performed acceptably. CONCLUSION: Because of its simplicity and ease of use, 1/X(2) is recommended for general application. If, however, instrument signal variance is too high to be managed by statistical techniques, the only solution is to control such variance through laboratory-based solutions. Published by Elsevier B.V.