The R Journal: article published in 2018, volume 10:1

Generalized Additive Model Multiple Imputation by Chained Equations With Package ImputeRobust
Daniel Salfran and Martin Spiess , The R Journal (2018) 10:1, pages 61-72.

Abstract Data analysis, common to all empirical sciences, often requires complete data sets. Unfortu nately, real world data collection will usually result in data values not being observed. We present a package for robust multiple imputation (the ImputeRobust package) that allows the use of generalized additive models for location, scale, and shape in the context of chained equations. The paper describes the basics of the imputation technique which builds on a semi-parametric regression model (GAMLSS) and the algorithms and functions provided with the corresponding package. Furthermore, some illustrative examples are provided.

Received: 2017-05-02; online 2018-05-16, supplementary material, (1.2 KiB)
CRAN packages: ImputeRobust, mice, gamlss
CRAN Task Views implied by cited CRAN packages: Econometrics, Multivariate, OfficialStatistics, SocialSciences

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-014,
  author = {Daniel Salfran and Martin Spiess},
  title = {{Generalized Additive Model Multiple Imputation by Chained
          Equations With Package ImputeRobust}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-014},
  url = {https://doi.org/10.32614/RJ-2018-014},
  pages = {61--72},
  volume = {10},
  number = {1}
}