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Improved likelihood ratio tests in a measurement error model for multivariate replicated data
Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Nanjing, Peoples R China.
Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Nanjing, Peoples R China.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Nanjing, Peoples R China.
2020 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 49, no 5, p. 1025-1042Article in journal (Refereed) Published
Abstract [en]

We present a measurement error model for multivariate replicated data and focus on the improved likelihood ratio tests for parameters of interest. By assuming that the random terms follow the scale mixtures of normal distributions, the model can bring robust inference and can target on both error-prone and error-free covariates. We derive modified versions from the original likelihood ratio statistics to achieve better asymptotic properties with high degree of accuracy. Simulation studies are conducted to display finite sample behavior as compared to the unmodified counterpart. The practical utility is illustrated through a root decomposition data.

Place, publisher, year, edition, pages
TAYLOR & FRANCIS INC , 2020. Vol. 49, no 5, p. 1025-1042
Keywords [en]
Auxiliary statistic, Hypothesis test, Likelihood ratio statistic, Robustness, Scale mixtures of normal distribution
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-403250DOI: 10.1080/03610926.2018.1554125ISI: 000506079000001OAI: oai:DiVA.org:uu-403250DiVA, id: diva2:1388703
Available from: 2020-01-27 Created: 2020-01-27 Last updated: 2020-01-27Bibliographically approved

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Jin, Shaobo

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