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seqimpute: Imputation of Missing Data in Sequence Analysis
Multiple imputation of missing data present in a dataset through the prediction based on either a random forest or a multinomial regression model. Covariates and time-dependent covariates can be included in the model. The prediction of the missing values is based on the method of Halpin (2012) <https://researchrepository.ul.ie/articles/report/Multiple_imputation_for_life-course_sequence_data/19839736>.
Getting started
Browse package contents
Package details |
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| Author | Kevin Emery [aut, cre], Anthony Guinchard [aut], Andre Berchtold [aut], Kamyar Taher [aut] |
| Maintainer | Kevin Emery <kevin.emery@unige.ch> |
| License | GPL-2 |
| Version | 2.0.0 |
| Package repository | View on CRAN |
| Installation |
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