Kurtosis tests for multivariate normality with monotone incomplete data

Tomoya Yamada (), Megan Romer () and Donald Richards ()

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2015, vol. 24, issue 3, 532-557

Abstract: We consider the problem of testing multivariate normality when the data consist of a random sample of two-step monotone incomplete observations. We define for such data a generalization of Mardia’s statistic for measuring kurtosis, derive the asymptotic non-null distribution of the statistic under certain regularity conditions and against a broad class of alternatives, and provide an application to a well-known data set on cholesterol measurements. Copyright Sociedad de Estadística e Investigación Operativa 2015

Keywords: Asymptotic expansion; Mardia’s statistic; Maximum likelihood estimation; Missing data; Monotone incomplete data; Regression imputation; Testing for multivariate normality; Primary 62C15; 62H10; Secondary 60D10; 62E15 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:testjl:v:24:y:2015:i:3:p:532-557

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DOI: 10.1007/s11749-014-0423-1

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