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  • 學位論文

線性確效評估之統計方法的研究

A Study on Statistical Methods for Evaluation of Linearity in Assay Validation

指導教授 : 劉仁沛

摘要


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並列摘要


Abstract Linearity is one of the most important characteristics for evaluation of the accuracy in assay validation. The current statistical method for evaluation of the linearity recommended by the Clinical Laboratory Standard Institute (CLSI) guideline EP6-A was reviewed. The method directly compares the point estimates with the pre-specified allowable limit and completely ignores the sampling error of the point estimates. An alternative method for evaluation of linearity proposed by Kroll, et al. (2000) considers the statistical test procedure based on the average deviation from linearity (ADL). However this procedure is based on the inappropriate formulation of hypothesis for evaluation of the linearity. Consequently, the type I error rates of both current methods may be inflated for inference of linearity. Because any procedures for assessment of linearity should be based on the sampling distributions of the proposed test statistics, we propose a generalized pivotal quantity (GPQ) procedure. The method does not involve in any nuisance parameters. The simulation studies were conducted to empirically compare the size and power between current and proposed methods. The simulation results show that the proposed methods not only adequately control size but also provide sufficient power. A numeric example illustrates the proposed methods.

參考文獻


[1] Chow, S.C. and Liu, J.P. (2000) Design and Analysis of Bioavailability and Bioequivalence Studies, 2nd Ed, Marcel Dekker, Inc. New York. Basel.
[3] International Conference on Harmonisation. (1994) ICH harmonised tripartite guideline, Q2A. Text on validation of analytical procedures. International Conference on Harmonisation, Geneva, Switzerland.
[4] International Conference on Harmonisation. (1996) ICH harmonised tripartite guideline, Q2B. Validation of analytical procedures: methodology. International Conference on Harmonisation, Geneva, Switzerland.
[9] Weerahandi, S. (2004) Generalized Inference in Repeated Measures. John Wiley & Sons Inc.
[10] Hsieh, E., Hsiao, C.F., and Liu, J.P. (2008) Statistical Inference for Evaluating the Linearity in Assay Validation.

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