miP

miP: Multiple Imputation Plots - R package using mainstream CRAN packages mice, mi, Amelia,.. Plots to visualize missing data and datasets that were produced by Multiple Imputation. The goal is is to visualize MI objects produced by the R packages mi, mice or Amelia II to provide a better understanding of the imputed data and to evaluate the MI process. This originated as result of Paul Brix’ master thesis with Anthony Unwin in Augsburg in 2011. As the package was archived in Spring 2015, and it seemed useful, Martin Maechler started maintaining it in November 2015. Slightly more generally, the goal is using mainstream and widely used CRAN packages for missing values’ data analysis, and more easily compare their methods, notably Multiple Imputation. Currently, results from mice, mi, and Amelia are (partly) supported.

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References in zbMATH (referenced in 1 article )

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  1. Xiaoyue Cheng and Dianne Cook and Heike Hofmann: Visually Exploring Missing Values in Multivariable Data Using a Graphical User Interface (2015) not zbMATH