期刊
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
卷 34, 期 1, 页码 79-96出版社
WILEY
DOI: 10.1002/cjs.5550340107
关键词
block empirical likelihood; confidence region; longitudinal data; partially linear regression model; semiparametric inference; Wilks theorem
The authors propose a block empirical likelihood procedure to accommodate the within-group correlation in longitudinal partially linear regression models. This leads them to prove a nonparametric version of the Wilks theorem. In comparison with normal approximations, their method does not require a consistent estimator for the asymptotic covariance matrix, which makes it easier to conduct inference on the parametric component of the model. An application to a longitudinal study on fluctuations of progesterone level in a menstrual cycle is used to illustrate the procedure developed here.
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