English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62378/95055 (66%)
Visitors : 2305483      Online Users : 44
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/122703


    Title: Use of a tolerance interval approach as a statistical quality control tool for traditional Chinese medicine
    Authors: Chiang, Chieh;Lai, Yi-Hsuan;Huang, Bo-Han;Guo, Wen-Jin;Wu, Yuh-Jenn;Chang, Lien-Cheng;Hsiao, Chin-Fu
    Keywords: Consistency;random-effects model;tolerance interval
    Date: 2020-05-12
    Issue Date: 2022-05-09 12:10:41 (UTC+8)
    Abstract: Raw materials for traditional Chinese medicine (TCM) are often from different resources and its final product may also be made by different sites. Therefore, variabilities from different resources such as site-to-site or within site component-to-component may be expected. Consequently, test for consistency in raw materials, in-process materials, and/or final product has become an important issue in the quality control (QC) process in TCM development. In this paper, a statistical QC process for raw materials and/or the final product of TCM is proposed based on a two sided β–content, γ–confidence tolerance interval. More specifically, we construct the tolerance interval for a random-effects model to assess the QC of TCM products from different regions and possibly different product batches. The products can be claimed to be consistency when the constructed tolerance interval is within the permitted range. Given the region and batch effects, sample sizes can also be calculated to ensure the desired measure of goodness. An example is presented to illustrate the proposed approach.
    Relation: Journal of biopharmaceutical statistics 30(5), p.873-881
    DOI: 10.1080/10543406.2020.1757693
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML17View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback