國家衛生研究院 NHRI:Item 3990099045/6286
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 912924      Online Users : 1174
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU 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: http://ir.nhri.org.tw/handle/3990099045/6286


    Title: Robust permutation tests for homogeneity of fingerprint patterns of dioxin congener profiles
    Other Titles: Environmetrics
    Authors: Chen, CC;Sen, PK;Wu, KY
    Contributors: Division of Biostatistics and Bioinformatics
    Abstract: Fingerprint analysis comparing the polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) congener profile patterns of collected samples with those of potential dioxin emission source(s) is an important tool for identifying environmental dioxin pollution. The constraint that the proportions of the 17 PCDD/F congeners comprising a fingerprint sum up to one motivates a multivariate gamma distribution, which leads to a Dirichlet distribution. Because of the complexity in restricted likelihood ratio tests and typical sample size limitations resulting from laboratory analysis costs, permutation test procedures are employed for hypothesis testing of the homogeneity of congener profiles. Pearson-type chi-squared tests based on the Dirichlet distribution (DM) assumption, the generalized form of DM using the arithmetic mean and geometric mean of the proportions, and the robust aligned rank test, are proposed and compared through simulations. PCDD/F samples collected from the stack of a local municipal solid waste incinerator and from ambient air near the municipal solid waste incinerator in Taiwan were illustrated as an example. The simulation results showed that the aligned rank test, followed by the DM-based test, was generally robust to distributional assumptions and had high statistical power. The arithmetic-mean-based and geometric-mean-based tests outperformed one another in different conditions, dependent on the underlying distribution.
    Date: 2012-06
    Relation: Environmetrics. 2012 Jun;23(4):285-294.
    Link to: http://dx.doi.org/10.1002/env.2137
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1180-4009&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000304439800002
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84862828016
    Appears in Collections:[Chu-Chih Chen] Periodical Articles

    Files in This Item:

    File Description SizeFormat
    PB2011120605.pdf229KbAdobe PDF596View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

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