淡江大學機構典藏:Item 987654321/99137
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62822/95882 (66%)
造访人次 : 4014844      在线人数 : 761
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/99137


    题名: When homogeneity meets heterogeneity: the geographically weighted regression with spatial lag approach to prenatal care utilization
    作者: Carla Shoff;Chen, Vivian Yi-Ju;Yang, Tse-Chuan
    贡献者: 淡江大學統計學系
    关键词: prenatal care;geographically weighted regression;spatial non-stationarity
    日期: 2014-05-01
    上传时间: 2014-10-15 14:28:02 (UTC+8)
    出版者: Naples: Universita degli Studi di Napoli "Federico II" * Facolta di Medicina Veterinaria
    摘要: Using geographically weighted regression (GWR), a recent study by Shoff and colleagues (2012) investigated the place-specific risk factors for prenatal care utilisation in the United States of America (USA) and found that most of the relationships between late or no prenatal care and its determinants are spatially heterogeneous. However, the GWR approach may be subject to the confounding effect of spatial homogeneity. The goal of this study was to address this concern by including both spatial homogeneity and heterogeneity into the analysis. Specifically, we employed an analytic framework where a spatially lagged (SL) effect of the dependent variable is incorporated into the GWR model, which is called GWR-SL. Using this framework, we found evidence to argue that spatial homogeneity is neglected in the study by Shoff et al. (2012) and that the results change after considering the SL effect of prenatal care utilisation. The GWR-SL approach allowed us to gain a placespecific understanding of prenatal care utilisation in USA counties. In addition, we compared the GWR-SL results with the results of conventional approaches (i.e., ordinary least squares and spatial lag models) and found that GWR-SL is the preferred modelling approach. The new findings help us to better estimate how the predictors are associated with prenatal care utilisation across space, and determine whether and how the level of prenatal care utilisation in neighbouring counties matters.
    關聯: Geospatial Health 8(2), pp.557-568
    DOI: 10.4081/gh.2014.45
    显示于类别:[統計學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML82检视/开启
    When homogeneity meets heterogeneity the geographically weighted regression with spatial lag approach to prenatal care utilization.pdf820KbAdobe PDF3检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

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