TY - JOUR
T1 - Goodness-of-fit tests for general linear models with covariates missed at random
AU - Guo, Xu
AU - Xu, Wangli
N1 - Funding Information:
The research was supported by the Fundamental Research Funds for the Central Universities , and the Research Funds of Renmin University of China ( No. 12XNI004 ).
Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/7
Y1 - 2012/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84863416409&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863416409&partnerID=8YFLogxK
U2 - 10.1016/j.jspi.2012.02.039
DO - 10.1016/j.jspi.2012.02.039
M3 - Article
AN - SCOPUS:84863416409
VL - 142
SP - 2047
EP - 2058
JO - Journal of Statistical Planning and Inference
JF - Journal of Statistical Planning and Inference
SN - 0378-3758
IS - 7
ER -