Provides imputation models and functions for binary or continuous Missing Not At Random (MNAR) outcomes through the use of the 'mice' package. The mice.impute.hecknorm() function provides imputation model for continuous outcome based on Heckman's model also named sample selection model as described in Galimard et al (2018) and Galimard et al (2016) <doi:10.1002/sim.6902>. The mice.impute.heckprob() function provides imputation model for binary outcome based on bivariate probit model as described in Galimard et al (2018).
| Version: | 1.0.2 |
| Depends: | R (≥ 3.2.1), mice (≥ 3.0.0) |
| Imports: | stats, mvtnorm, pbivnorm, GJRM, sampleSelection |
| Published: | 2018-08-27 |
| Author: | Jacques-Emmanuel Galimard [aut, cre] (INSERM, U1153, ECSTRA team), Matthieu Resche-Rigon [aut] (INSERM, U1153, ECSTRA team) |
| Maintainer: | Jacques-Emmanuel Galimard <jacques-emmanuel.galimard at inserm.fr> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| In views: | MissingData |
| CRAN checks: | miceMNAR results |
| Reference manual: | miceMNAR.pdf |
| Package source: | miceMNAR_1.0.2.tar.gz |
| Windows binaries: | r-devel: miceMNAR_1.0.2.zip, r-release: miceMNAR_1.0.2.zip, r-oldrel: miceMNAR_1.0.2.zip |
| macOS binaries: | r-release: miceMNAR_1.0.2.tgz, r-oldrel: miceMNAR_1.0.2.tgz |
| Old sources: | miceMNAR archive |
Please use the canonical form https://CRAN.R-project.org/package=miceMNAR to link to this page.