Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147534 | Journal of Statistical Planning and Inference | 2012 | 12 Pages |
Abstract
In this paper, we consider a model checking problem for general linear models with randomly missing covariates. Two types of score type tests with inverse probability weight, which is estimated by parameter and nonparameter methods respectively, are proposed to this goodness of fit problem. The asymptotic properties of the test statistics are developed under the null and local alternative hypothesis. Simulation study is carried out to present the performance of the sizes and powers of the tests. We illustrate the proposed method with a data set on monozygotic twins.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Xu Guo, Wangli Xu,