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- W2891683903 abstract "Item nonresponse is frequently encountered in practice. Ignoring missing data can lose efficiency and lead to misleading inference. Fractional imputation is a frequentist approach of imputation for handling missing data. However, the parametric fractional imputation of cite{kim2011parametric} may be subject to bias under model misspecification. In this paper, we propose a novel semiparametric fractional imputation method using Gaussian mixture models. The proposed method is computationally efficient and leads to robust estimation. The proposed method is further extended to incorporate the categorical auxiliary information. The asymptotic model consistency and $sqrt{n}$- consistency of the semiparametric fractional imputation estimator are also established. Some simulation studies are presented to check the finite sample performance of the proposed method." @default.
- W2891683903 created "2018-09-27" @default.
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- W2891683903 date "2018-09-16" @default.
- W2891683903 modified "2023-10-18" @default.
- W2891683903 title "Semiparametric fractional imputation using Gaussian mixture models for handling multivariate missing data" @default.
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- W2891683903 doi "https://doi.org/10.48550/arxiv.1809.05976" @default.
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