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    题名: Assessment of Modelling Longitudinal Binary Data Based on Graphical Methods
    作者: Lin, Kuo-Chin;Chen, Yi-Ju
    关键词: GEE;Goodness-of-fit;Kernel smoothing;Local mean deviance plot;Longitudinal binary response;Marginal model plot
    日期: 2017-02-01
    上传时间: 2017-07-04 02:11:28 (UTC+8)
    出版者: Taylor & Francis Inc.
    摘要: Longitudinal categorical data are commonly applied in a variety of fields and are frequently analyzed by generalized estimating equation (GEE) method. Prior to making further inference based on the GEE model, the assessment of model fit is crucial. Graphical techniques have long been in widespread use for assessing the model adequacy. We develop alternative graphical approaches utilizing plots of marginal model-checking condition and local mean deviance to assess the GEE model with logit link for longitudinal binary responses. The applications of the proposed procedures are illustrated through two longitudinal binary datasets.
    關聯: Communications in Statistics-Theory and Methods 46(7), p.3426–3437
    DOI: 10.1080/03610926.2015.1062107
    显示于类别:[統計學系暨研究所] 期刊論文

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