Prediction Intervals for Weighted Deming Regression

Music City Center 

We have developed a methodology for the estimation of the prediction interval associated with Deming regression. Deming regression is a common methodology of analysis to compare the linearly correlated measurements from two methods, X and Y, over an interval[a,b]. The methodology applies to X and Y measurements whose variance is constant, or linearly, and quadratically increasing with respect to their mean over the interval. The prediction interval invokes the key term, variance of Y, which is a function of the regression parameters and the error terms, and their variances and co-variances. For each measurement variance case, we calculated the coverage of the prediction interval on data generated by simulation. We found that for the linear case, the methodology needs an adjustment k, whose function incorporates a, b, and the prediction level. The methodology applied to X and Y paired data generated by simulation shows coverage rates within 2% of the prescribed 90% and 95% prediction intervals. We present this methodology to complement those found in CLSI EP09 and EP14 for method comparison and commutability studies, respectively.

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Section on Medical Devices and Diagnostics