Process and analyze Electronic Health Record (EHR) data. Frequency and contingency tables for many binary outcomes and a binary exposure variable can be generated more efficiently. Phenome Wide Association Study (PheWAS) performed using EHR data can be analyzed using three commonly used statistical analysis methods: Firth's penalized-likelihood logistic regression; logistic regression with likelihood ratio test; conventional logistic regression with Wald test.
| Version: | 0.1-3 |
| Depends: | R (≥ 2.10) |
| Imports: | stats, utils, logistf |
| Suggests: | glmnet |
| Published: | 2017-10-20 |
| Author: | Leena Choi [aut, cre], Cole Beck [aut] |
| Maintainer: | Leena Choi <naturechoi at gmail.com> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| CRAN checks: | EHR results |
| Reference manual: | EHR.pdf |
| Package source: | EHR_0.1-3.tar.gz |
| Windows binaries: | r-devel: EHR_0.1-3.zip, r-release: EHR_0.1-3.zip, r-oldrel: EHR_0.1-3.zip |
| macOS binaries: | r-release: EHR_0.1-3.tgz, r-oldrel: EHR_0.1-3.tgz |
Please use the canonical form https://CRAN.R-project.org/package=EHR to link to this page.