Abstract
In this paper, we consider the one-sample problem of testing for the subvector of a mean vector with two-step monotone missing data. In the case that the data set consists of complete data with dimensions and incomplete data with dimensions, we derive the likelihood ratio criterion for testing the mean vector under the given mean vector of dimensions. Furthermore, we propose an approximation for the upper percentile of the likelihood ratio test (LRT) statistic. We investigate the accuracy and asymptotic behavior of this approximation using Monte Carlo simulation. An example is presented in order to illustrate the method.
Funding Statement
Second author’s research was in part supported by Grant-in-Aid for Scientific Research (C) (26330050).
Acknowledgments
The authors would like to thank the referee for helpful comments and suggestions.
Citation
Tamae Kawasaki. Takashi Seo. "A test for subvector of mean vector with two-step monotone missing data." SUT J. Math. 52 (1) 21 - 39, June 2016. https://doi.org/10.55937/sut/1469055995
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