教師資料查詢 | 類別: 期刊論文 | 教師: 陳怡如 Chen Yi-ju (瀏覽個人網頁)

標題:A nonparametric smoothing method for assessing GEE models with longitudinal binary data
學年97
學期1
出版(發表)日期2008/09/01
作品名稱A nonparametric smoothing method for assessing GEE models with longitudinal binary data
作品名稱(其他語言)
著者Lin, Kuo-Chin; 陳怡如; Chen, Yi-ju; Shyr, Yu
單位淡江大學統計學系
出版者West Sussex: John Wiley & Sons Ltd.
著錄名稱、卷期、頁數Statistics in Medicine 27(22), pp.4428-4439
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 the 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 (Biometrics 1991; 47:1267-1282). 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.
關鍵字GEE model; goodness-of-fit test; logistic regression model; longitudinal binary data; nonparametric smoothing
語言英文
ISSN0277-6715
期刊性質
收錄於SCI
產學合作
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審稿制度
國別英國
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