Correct identification and handling of missing data is one of the most important steps in any analysis. To aid this process, 'mde' provides a very easy to use yet robust framework to quickly get an idea of where the missing data lies and therefore find the most appropriate action to take. Graham WJ (2009) <doi:10.1146/annurev.psych.58.110405.085530>.
| Version: | 0.2.1 |
| Depends: | R (≥ 3.6.0) |
| Imports: | dplyr (≥ 0.8.9), tidyr (≥ 1.0.3) |
| Suggests: | knitr, rmarkdown, testthat, covr |
| Published: | 2020-06-27 |
| Author: | Nelson Gonzabato [aut, cre] |
| Maintainer: | Nelson Gonzabato <gonzabato at hotmail.com> |
| BugReports: | https://github.com/Nelson-Gon/mde/issues |
| License: | GPL-3 |
| URL: | https://github.com/Nelson-Gon/mde |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | mde results |
| Reference manual: | mde.pdf |
| Vignettes: |
mde-Missing-Data-Explorer |
| Package source: | mde_0.2.1.tar.gz |
| Windows binaries: | r-devel: mde_0.2.1.zip, r-release: mde_0.2.1.zip, r-oldrel: mde_0.2.1.zip |
| macOS binaries: | r-release: mde_0.2.1.tgz, r-oldrel: mde_0.2.1.tgz |
| Old sources: | mde archive |
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