ESTIMATION OF THE LINEAR RELATIONSHIP BETWEEN THE MEASUREMENTS OF 2 METHODS WITH PROPORTIONAL ERRORS

被引：118

作者：

LINNET, K

机构：

[1] Department of Clinical Chemistry, KK 7642, Rigshospitalet, University of Copenhagen, Copenhagen, DK-2100

来源：

STATISTICS IN MEDICINE | 1990年 / 9卷 / 12期

关键词：

D O I：

10.1002/sim.4780091210

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The linear relationship between the measurements of two methods is estimated on the basis of a weighted errors‐in‐variables regression model that takes into account a proportional relationship between standard deviations of error distributions and true variable levels. Weights are estimated by an iterative procedure. As shown by simulations, the regression procedure yields practically unbiased slope estimates in realistic situations. Standard errors of slope and location difference estimates are derived by the jackknife principle. For illustration, the linear relationship is estimated between the measurements of two albumin methods with proportional errors. Copyright © 1990 John Wiley & Sons, Ltd.

引用

页码：1463 / 1473

页数：11

共 20 条

[1] Statistical Methods, 6, (1967)
[2] Kendall M.G., Stuart A., The Advanced Theory of Statistics, 2, (1961)
[3] Hald A., Statistical Theory with Engineering Applications, (1952)
[4] Cornbleet P.J., Gochman N., Incorrect least‐squares regression coefficients in method‐comparison analysis, Clinical Chemistry, 25, pp. 432-438, (1979)
[5] Ross J.W., Fraser M.D., The effect of analyte and analyte concentration upon precision estimates in clinical chemistry, American Journal of Clinical Pathology, 66, pp. 193-205, (1976)
[6] Kay C., Nix A.B.J., Kemp K.W., Rowlands R.J., Richards G., Groom G.V., Griffiths K., Wilson D.W., Dose‐interpolation of immunoassay data: uncertainties associated with curve‐fitting, Statistics in Medicine, 5, pp. 183-192, (1986)
[7] Textbook of Clinical Chemistry, (1986)
[8] Kelly G.E., Use of the structural equations model in assessing the reliability of a new measurement technique, Applied Statistics, 34, pp. 258-263, (1985)
[9] Sprent P., A generalized least‐squares approach to linear functional relationships (with discussion), Journal of the Royal Statistical Society, Series B, 28, pp. 278-297, (1966)
[10] Barnett V.D., Fitting straight lines‐The linear functional relationship with replicated observations, Applied Statistics, 19, pp. 135-144, (1970)

← 1 2 →