JSM 2005 - Toronto

Abstract #304082

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 184
Type: Topic Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #304082
Title: Multiple Assay Methods Comparison
Author(s): Abha Sharma*+
Companies: Roche
Address: 4300 Hacienda Drive, Pleasanton, CA, 94588, United States
Keywords: Curvilinear Calibration ; Heteroscedasticity ; Multiplicative Interaction ; Singular Value Decompositon ; ANOVA ; Regression
Abstract:

When p(> 2) assay methods are compared, an adaptation of Mandel's model can be used to model complex differences between assays and to highlight heteroscedasticity. The model is y(ij) = Sample(i) + Method(j) + Sample(i)*Slope(j) + S1(i)*M1(j) + S2(i)*M2(j) + E(ij). Here, y(ij) stands for the assay of sample i by method j, Sample(i) is the true value for ith patient sample, Method(j) is the overall bias of the assay method j, Sample(i)*Slope(j) measures the nonparallelism in the linear calibration of different assay methods, and S1(i)*M1(j) and S2(i)*M2(j) are multiplicative interaction (MI) terms. These can model curvature in calibration of an assay method and also isolate heteroscedasticity. This model is fitted starting with a conventional, unreplicated, two-way ANOVA for the two main effects. Regressing each column of the residual matrix on the estimated row main effect gives the nonparallelism term. Next, the singular value decomposition (SVD) of the matrix of residuals from this "column regression" model gives the estimates of the two MI terms. Model diagnosis consists of determining how many elaborations are needed and interpreting the fitted coefficients.

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