AdhereR: Adherence to Medications
Computation of adherence to medications from Electronic Health care
Data and visualization of individual medication histories and adherence
patterns. The package implements a set of S3 classes and
functions consistent with current adherence guidelines and definitions.
It allows the computation of different measures of
adherence (as defined in the literature, but also several original ones),
their publication-quality plotting,
the estimation of event duration and time to initiation,
the interactive exploration of patient medication history and
the real-time estimation of adherence given various parameter settings.
It scales from very small datasets stored in flat CSV files to very large
databases and from single-thread processing on mid-range consumer
laptops to parallel processing on large heterogeneous computing clusters.
It exposes a standardized interface allowing it to be used from other
programming languages and platforms, such as Python.
| Version: |
0.8.1 |
| Depends: |
R (≥ 3.0) |
| Imports: |
lubridate (≥ 1.5), parallel (≥ 3.0), data.table (≥ 1.9), rsvg (≥ 1.3), jpeg (≥ 0.1), png (≥ 0.1), webp (≥ 1.0), methods |
| Suggests: |
rmarkdown (≥ 1.1), knitr (≥ 1.20), R.rsp (≥ 0.40), base64 (≥ 2.0), viridisLite (≥ 0.4), AdhereRViz (≥ 0.2) |
| Published: |
2022-07-05 |
| DOI: |
10.32614/CRAN.package.AdhereR |
| Author: |
Dan Dediu [aut, cre],
Alexandra Dima [aut],
Samuel Allemann [aut] |
| Maintainer: |
Dan Dediu <ddediu at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/ddediu/AdhereR |
| NeedsCompilation: |
no |
| Citation: |
AdhereR citation info |
| CRAN checks: |
AdhereR results |
Documentation:
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