Advanced Search

Ariadne Pfad:



Multiple imputation of multilevel missing data: An introduction to the R package pan
SourceSAGE Open 6 (2016) 4, S. 1-17 ZDB
Document  (722 KB)
License of the document Lizenz-Logo 
Keywords (German)
Document typeArticle (journal)
ISSN2158-2440; 21582440
Year of creation
review statusPeer-Reviewed
Abstract (English):The treatment of missing data can be difficult in multilevel research because state-of-the-art procedures such as multiple imputation (MI) may require advanced statistical knowledge or a high degree of familiarity with certain statistical software. In the missing data literature, pan has been recommended for MI of multilevel data. In this article, we provide an introduction to MI of multilevel missing data using the R package pan, and we discuss its possibilities and limitations in accommodating typical questions in multilevel research. To make pan more accessible to applied researchers, we make use of the mitml package, which provides a user-friendly interface to the pan package and several tools for managing and analyzing multiply imputed data sets. We illustrate the use of pan and mitml with two empirical examples that represent common applications of multilevel models, and we discuss how these procedures may be used in conjunction with other software.
Date of publication27.01.2017
CitationGrund, Simon; Lüdtke, Oliver; Robitzsch, Alexander: Multiple imputation of multilevel missing data: An introduction to the R package pan - In: SAGE Open 6 (2016) 4, S. 1-17 - URN: urn:nbn:de:0111-pedocs-126928 - DOI: 10.25656/01:12692; 10.1177/2158244016668220
export files

share content at social platforms