A Nonparametric Test of Missing Completely at Random for Inc…
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- DOI 10.1007/s11336-014-9410-4
- PMID https://pubmed.ncbi.nlm.nih.gov/25080867
- OpenAlex ID W2068630645
- Type Article
- Language EN
- Published 31 Jul 2014
- Volume 80 (3)
- Pages 707–726
- Source Psychometrika
- Publisher Springer Science+Business Media
- FWCI 1.06
- Countries 1
- Institutions 1
- Added 24 Jun 2016
- Updated 16 Oct 2026
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A Nonparametric Test of Missing Completely at Random for Incomplete Multivariate Data
Article 2014 EN
Missing data occur in many real world studies. Knowing the type of missing mechanisms is important for adopting appropriate statistical analysis procedure. Many statistical methods assume missing completely at random (MCAR) due to its simplicity. Therefore, it is necessary to test whether this assumption is satisfied before applying those procedures. In the literature, most of the procedures for t…
25
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2 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Jun Li Corresponding | University of California, Rive… (US) | |
| 2 | Yao Yu | University of California, Rive… (US) | — |
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