劉仁沛Liu, Jen-Pei臺灣大學:農藝學研究所吳惠娟Wu, Huei-JyuanHuei-JyuanWu2010-05-052018-07-112010-05-052018-07-112008U0001-2207200801451600http://ntur.lib.ntu.edu.tw//handle/246246/180058Abstractinearity 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.Contents Introduction 1 Literature Review 4.1 Experiment Design 4.2 Current Test Procedures 5.2.1 The Average Deviation from Linearity (ADL) 5.2.2 Corrected Kroll''s Method 6.2.3 The Approved CLSI EP6-A Method 8.2.4 Hsieh''s Method 9 Proposed Methods 11.1 Type I and Type II Errors in Evaluation of Linearity 11.2 Testing Hypothesis 12.3 The Multivariate Normal Distribution 13.4 Generalized Pivotal Quantity(GPQ) 15 Simulation Study 19.1 Parameter Combinations 19.2 Simulation Process 19.3 Simulation Results 20 Numerical Example 23 Summary and Discussion 25.1 Summary 25.2 Why We Have the Proposed Method 25.3 Why Linearity Is Important 26eference 27ppendices 29application/pdf469443 bytesapplication/pdfen-US允許區間線性量化分析的實驗方法Allowable LimitLinearityQuantitative analytical laboratorythesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/180058/1/ntu-97-R95621209-1.pdf