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    篇名/題名:A nonparametric smoothing method for assessing GEE models with binary longitudinal data
    摘要:Studies involving
    longitudinal binary responses are widely applied in the health and
    biomedical sciences research, and frequently analyzed by
    generalized estimating equations (GEE) method. This article
    proposes an alternative goodness-of-fit test based on
    nonparametric smoothing approach for assessing the adequacy of GEE
    fitted models, which can be regarded as an extension of the
    goodness-of-fit test of le Cessie and van Houwelingen [1]. The
    expectation and approximate variance of the proposed test
    statistic are derived. The asymptotic distribution of the proposed
    test statistic in terms of a scaled chi-squared distribution and
    the power performance of the proposed test are discussed by
    simulation studies. The testing procedure is demonstrated by two
    real data.
    類型:期刊論文
    西元出版年:2011
    著作語言:en
    作者:Lin, K. C.、Chen, Y.J.、Shyr, Y.
    學校系所:企業管理系