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 goodness-of-fit test for logistic-normal models using nonparametric smoothing method
學年99
學期2
出版(發表)日期2011/02/01
作品名稱A goodness-of-fit test for logistic-normal models using nonparametric smoothing method
作品名稱(其他語言)
著者Lin, Kuo-Chin; Chen, Yi-Ju
單位淡江大學統計學系
出版者Amsterdam: Elsevier BV * North-Holland
著錄名稱、卷期、頁數Journal of Statistical Planning and Inference 141(2), pp.1069-1076
摘要Logistic-normal models can be applied for analysis of longitudinal binary data. The aim of this article is to propose a goodness-of-fit test using nonparametric smoothing techniques for checking the adequacy of logistic-normal models. Moreover, the leave-one-out cross-validation method for selecting the suitable bandwidth is developed. The quadratic form of the proposed test statistic based on smoothing residuals provides a global measure for checking the model with categorical and continuous covariates. The formulae of expectation and variance of the proposed statistics are derived, and their asymptotic distribution is approximated by a scaled chi-squared distribution. The power performance of the proposed test for detecting the interaction term or the squared term of continuous covariates is examined by simulation studies. A longitudinal dataset is utilized to illustrate the application of the proposed test.
關鍵字Goodness-of-fit; Logistic-normal models; Longitudinal binary data; Nonparametric smoothing
語言英文
ISSN0378-3758
期刊性質國外
收錄於SCI
產學合作
通訊作者Lin, Kuo-Chin
審稿制度
國別荷蘭
公開徵稿
出版型式紙本
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