A comparison of model-based imputation methods for handling missing predictor values in a linear regression model: A simulation study
In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likeli...
| Published in: | AIP Conference Proceedings |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
| Published: |
American Institute of Physics Inc.
2017
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028346649&doi=10.1063%2f1.4995930&partnerID=40&md5=92f9ba68656bd545d34b8ab0716797e9 |