Tests of Homoscedasticity, Normality, and Missing Completely at Random for Incomplete Multivariate Data
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DOI: 10.1007/s11336-010-9175-3
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References listed on IDEAS
- Kevin Kim & Peter Bentler, 2002. "Tests of homogeneity of means and covariance matrices for multivariate incomplete data," Psychometrika, Springer;The Psychometric Society, vol. 67(4), pages 609-623, December.
- Mortaza Jamshidian & Peter M. Bentler, 1999. "ML Estimation of Mean and Covariance Structures with Missing Data Using Complete Data Routines," Journal of Educational and Behavioral Statistics, , vol. 24(1), pages 21-24, March.
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- Chassan, Malika & Concordet, Didier, 2023. "How to test the missing data mechanism in a hidden Markov model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
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- Jamshidian, Mortaza & Jalal, Siavash & Jansen, Camden, 2014. "MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i06).
- Jun Li & Yao Yu, 2015. "A Nonparametric Test of Missing Completely at Random for Incomplete Multivariate Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 707-726, September.
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- Frahm, Gabriel & Nordhausen, Klaus & Oja, Hannu, 2020. "M-estimation with incomplete and dependent multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
- Serguei Rouzinov & André Berchtold, 2022. "Regression-Based Approach to Test Missing Data Mechanisms," Data, MDPI, vol. 7(2), pages 1-28, January.
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Keywords
covariance structures; k-sample test; missing data; multiple imputation; nonparametric test; structural equations; test of homogeneity of covariances;All these keywords.
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