Corpus ID: 10201308

A multivariate technique for multiply imputing missing values using a sequence of regression models

@article{Raghunathan2001AMT,
  title={A multivariate technique for multiply imputing missing values using a sequence of regression models},
  author={Trivellore E. Raghunathan and James M. Lepkowski and John Van Hoewyk and Peter W. Solenberger},
  journal={Survey Methodology},
  year={2001},
  volume={27},
  pages={85-95}
}
This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. The types of regression models used are linear, logistic, Poisson, generalized logit or a mixture of these depending on the type of variable being imputed. Two additional common features in the imputation… Expand
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