Hypothesis test on response mean with inequality constraints under data missing when covariables are present

Hong-Xia Xu, Guo-Liang Fan and Han-Ying Liang ()
Additional contact information
Hong-Xia Xu: Zhejiang Gongshang University
Guo-Liang Fan: Anhui Polytechnic University
Han-Ying Liang: Tongji University

Statistical Papers, 2017, vol. 58, issue 1, No 4, 53-75

Abstract: Abstract This paper addresses the problem of hypothesis test on response mean with various inequality constraints in the presence of covariates when response data are missing at random. The various hypotheses include to test single point, two points, set of inequalities as well as two-sided set of inequalities of the response mean. The test statistics is constructed by the weighted-corrected empirical likelihood function of the response mean based on the approach of weighted-corrected imputation for the response variable. We investigate limiting distributions and asymptotic powers of the proposed empirical likelihood ratio test statistics with auxiliary information. The results show that the test statistics with auxiliary information is more efficient than that without auxiliary information. A simulation study is undertaken to investigate the finite sample performance of the proposed method.

Keywords: Auxiliary information; Empirical likelihood; Hypothesis test; Inequality constraint; Missing data; Response mean; 62G10; 62G20 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s00362-015-0687-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stpapr:v:58:y:2017:i:1:d:10.1007_s00362-015-0687-x

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-015-0687-x

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().