Checking the adequacy of partial linear models with missing covariates at random |
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Authors: | Wangli Xu Xu Guo |
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Institution: | 1. Center for Applied Statistics, School of Statistics, Renmin University of China, Zhongguancun Street 59, Beijing, 100872, China 2. Department of Mathematics, Hong Kong Baptist University, Fong Shu-Chuen Library 1110, Kowloon Tong, Hong Kong
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Abstract: | In this paper, we consider the goodness-of-fit for checking whether the nonparametric function in a partial linear regression model with missing covariate at random is a parametric one or not. We estimate the selection probability by using parametric and nonparametric approaches. Two score type tests are constructed with the estimated selection probability. The asymptotic distributions of the test statistics are investigated under the null and local alterative hypothesis. Simulation studies are carried out to examine the finite sample performance of the sizes and powers of the tests. We apply the proposed procedure to a data set on the AIDS clinical trial group (ACTG 315) study. |
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