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A SAS Macro for Deming Regression
This paper was presented at SESUG 2009: http://analytics.ncsu.edu/sesug/2009/CC014.Deal.pdf
In method-comparison studies, regression analysis is often used to estimate the systematic difference between measurements from two different methods. Ordinary linear regression should only be used if the measurements from one of the methods are without random error, which rarely occurs. The Deming method of regression analysis, which accounts for measurement error in both methods, is often more appropriate, and is requested by the U.S. Food and Drug Administration (FDA) in medical device submissions. Though PROC NLP and CALIS in SAS® can accommodate Deming regression models, these procedures are not widely used, and may not be easily understood by many applied statisticians. This paper will present a macro that uses multiple DATA steps and PROC MEANS statements to calculate the slope and intercept of the Deming regression line. Since it is difficult to derive a formula for the standard deviations of these estimates, the non-parametric jackknife method is employed to construct confidence intervals.