TY - JOUR
AU - Gochman,, N
AB - Abstract The least-squares method is frequently used to calculate the slope and intercept of the best line through a set of data points. However, least-squares regression slopes and intercepts may be incorrect if the underlying assumptions of the least-squares model are not met. Two factors in particular that may result in incorrect least-squares regression coefficients are: (a) imprecision in the measurement of the independent (x-axis) variable and (b) inclusion of outliers in the data analysis. We compared the methods of Deming, Mandel, and Bartlett in estimating the known slope of a regression line when the independent variable is measured with imprecision, and found the method of Deming to be the most useful. Significant error in the least-squares slope estimation occurs when the ratio of the standard deviation of measurement of a single x value to the standard deviation of the x-data set exceeds 0.2. Errors in the least-squares coefficients attributable to outliers can be avoided by eliminating data points whose vertical distance from the regression line exceed four times the standard error the estimate. This content is only available as a PDF. © 1979 The American Association for Clinical Chemistry, Inc. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Incorrect least-squares regression coefficients in method-comparison analysis.
JF - Clinical Chemistry
DO - 10.1093/clinchem/25.3.432
DA - 1979-03-01
UR - https://www.deepdyve.com/lp/oxford-university-press/incorrect-least-squares-regression-coefficients-in-method-comparison-XAx2piJS2v
SP - 432
EP - 438
VL - 25
IS - 3
DP - DeepDyve
ER -