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Comparison of alternative imputation methods for ordinal data
- Source :
- Communications in Statistics - Simulation and Computation. 46:315-330
- Publication Year :
- 2014
- Publisher :
- Informa UK Limited, 2014.
-
Abstract
- In this article, we compare alternative missing imputation methods in the presence of ordinal data, in the framework of CUB (Combination of Uniform and (shifted) Binomial random variable) models. Various imputation methods are considered, as are univariate and multivariate approaches. The first step consists of running a simulation study designed by varying the parameters of the CUB model, to consider and compare CUB models as well as other methods of missing imputation. We use real datasets on which to base the comparison between our approach and some general methods of missing imputation for various missing data mechanisms.
- Subjects :
- Statistics and Probability
Ordinal data
Multivariate statistics
Statistics::Applications
Missing data
05 social sciences
Univariate
050401 social sciences methods
computer.software_genre
01 natural sciences
CUB models
Binomial distribution
010104 statistics & probability
0504 sociology
Single imputation
Modeling and Simulation
Statistics
Statistics::Methodology
Imputation (statistics)
Data mining
0101 mathematics
computer
Mathematics
Subjects
Details
- ISSN :
- 15324141 and 03610918
- Volume :
- 46
- Database :
- OpenAIRE
- Journal :
- Communications in Statistics - Simulation and Computation
- Accession number :
- edsair.doi.dedup.....dc4f4ec8abd4a61b5e02a2ce120160c7