Statistical Inference in Missing Data by MCMC and Non-MCMC Multiple Imputation Algorithms: Assessing the Effects of Between-Imputation Iterations
Incomplete data are ubiquitous in social sciences; as a consequence, available data are inefficient (ineffective) and often biased. In the literature, multiple imputation is known to be the standard method to handle missing data. While the theory of multiple imputation has been known for decades, th...
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2017-07-01
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| Series: | Data Science Journal |
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| Online Access: | https://datascience.codata.org/articles/690 |