Exact two‐sided tolerance interval controlling tail proportions for sample variances

2020 ◽  
Vol 36 (3) ◽  
pp. 1074-1085 ◽  
Author(s):  
Baocai Guo ◽  
Naifan Zhu ◽  
Wei Wang ◽  
Yurong Song ◽  
Hsiuying Wang
Keyword(s):  
Tolerance Interval ◽  
Sample Variances

Approximate two-sided tolerance interval for sample variances

2019 ◽  
Vol 32 (1) ◽  
pp. 10-24 ◽  
Author(s):  
Yuhui Yao ◽  
Martin G. C. Sarmiento ◽  
Subha Chakraborti ◽  
Eugenio K. Epprecht
Keyword(s):  
Tolerance Interval ◽  
Sample Variances

Biometeorological norm as tolerance interval of man to weather stimuli

1981 ◽  
Vol 25 (2) ◽  
pp. 123-126 ◽  
Author(s):  
Maria Baranowska ◽  
B. Gabryl
Keyword(s):  
Tolerance Interval

scholarly journals Quantitation of 35S Promoter in Maize DNA Extracts from Genetically Modified Organisms Using Real-Time Polymerase Chain Reaction, Part 2: Interlaboratory Study

2005 ◽  
Vol 88 (2) ◽  
pp. 558-573 ◽  
Author(s):  
Max Feinberg ◽  
Sophie Fernandez ◽  
Sylvanie Cassard ◽  
Chrystèle Charles-Delobel ◽  
Yves Bertheau ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Real Time ◽  
Genetically Modified Organisms ◽  
Genetically Modified ◽  
Interlaboratory Study ◽  
Performance Criteria ◽  
Tolerance Interval ◽  
Chain Reaction ◽  
Qrt Pcr ◽  
Polymerase Chain

Abstract The European Committee for Standardization (CEN) and the European Network of GMO Working Laboratories have proposed development of a modular strategy for stepwise validation of complex analytical techniques. When applied to the quantitation of genetically modified organisms (GMOs) in food products, the instrumental quantitation step of the technique is separately validated from the DNA extraction step to better control the sources of uncertainty and facilitate the validation of GMO-specific polymerase chain reaction (PCR) tests. This paper presents the results of an interlaboratory study on the quantitation step of the method standardized by CEN for the detection of a regulatory element commonly inserted in GMO maize-based foods. This is focused on the quantitation of P35S promoter through using the quantitative real-time PCR (QRT-PCR). Fifteen French laboratories participated in the interlaboratory study of the P35S quantitation operating procedure on DNA extract samples using either the thermal cycler ABI Prism® 7700 (Applied Biosystems, Foster City, CA) or Light Cycler® (Roche Diagnostics, Indianapolis, IN). Attention was focused on DNA extract samples used to calibrate the method and unknown extract samples. Data were processed according to the recommendations of ISO 5725 standard. Performance criteria, obtained using the robust algorithm, were compared to the classic data processing after rejection of outliers by the Cochran and Grubbs tests. Two laboratories were detected as outliers by the Grubbs test. The robust precision criteria gave values between the classical values estimated before and after rejection of the outliers. Using the robust method, the relative expanded uncertainty by the quantitation method is about 20% for a 1% Bt176 content, whereas it can reach 40% for a 0.1% Bt176. The performances of the quantitation assay are relevant to the application of the European regulation, which has an accepted tolerance interval of about ±50%. These data were fitted to a power model (r2 = 0.96). Thanks to this model, it is possible to propose an estimation of uncertainty of the QRT-PCR quantitation step and an uncertainty budget depending on the analytical conditions.

scholarly journals Confidence and coverage for Bland–Altman limits of agreement and their approximate confidence intervals

2016 ◽  
Vol 27 (5) ◽  
pp. 1559-1574 ◽  
Author(s):  
Andrew Carkeet ◽  
Yee Teng Goh
Keyword(s):  
Confidence Intervals ◽  
Small Sample ◽  
Interval Methods ◽  
Tolerance Interval ◽  
Confidence Limits ◽  
Sample Sizes ◽  
Limits Of Agreement ◽  
Approximate Methods ◽  
Exact Confidence Intervals ◽  
Tolerance Factors

Bland and Altman described approximate methods in 1986 and 1999 for calculating confidence limits for their 95% limits of agreement, approximations which assume large subject numbers. In this paper, these approximations are compared with exact confidence intervals calculated using two-sided tolerance intervals for a normal distribution. The approximations are compared in terms of the tolerance factors themselves but also in terms of the exact confidence limits and the exact limits of agreement coverage corresponding to the approximate confidence interval methods. Using similar methods the 50th percentile of the tolerance interval are compared with the k values of 1.96 and 2, which Bland and Altman used to define limits of agreements (i.e. [Formula: see text]+/− 1.96Sd and [Formula: see text]+/− 2Sd). For limits of agreement outer confidence intervals, Bland and Altman’s approximations are too permissive for sample sizes <40 (1999 approximation) and <76 (1986 approximation). For inner confidence limits the approximations are poorer, being permissive for sample sizes of <490 (1986 approximation) and all practical sample sizes (1999 approximation). Exact confidence intervals for 95% limits of agreements, based on two-sided tolerance factors, can be calculated easily based on tables and should be used in preference to the approximate methods, especially for small sample sizes.

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