Package: CIMPLE 0.1.0
Howard Baik
CIMPLE: Analysis of Longitudinal Electronic Health Record (EHR) Data with Possibly Informative Observational Time
Analyzes longitudinal Electronic Health Record (EHR) data with possibly informative observational time. These methods are grouped into two classes depending on the inferential task. One group focuses on estimating the effect of an exposure on a longitudinal biomarker while the other group assesses the impact of a longitudinal biomarker on time-to-diagnosis outcomes. The accompanying paper is Du et al (2024) <doi:10.48550/arXiv.2410.13113>.
Authors:
CIMPLE_0.1.0.tar.gz
CIMPLE_0.1.0.tar.gz(r-4.5-noble)CIMPLE_0.1.0.tar.gz(r-4.4-noble)
CIMPLE_0.1.0.tgz(r-4.4-emscripten)CIMPLE_0.1.0.tgz(r-4.3-emscripten)
CIMPLE.pdf |CIMPLE.html✨
CIMPLE/json (API)
NEWS
| # Install 'CIMPLE' in R: |
| install.packages('CIMPLE', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- long_data - Long_data
- surv_data - Long_data
- train_data - Long_data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 months agofrom:032f33b557. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 13 2024 |
| R-4.5-linux | OK | Dec 13 2024 |
Dependencies:backportsbitbit64bootbroomclicliprcodacodetoolscolorspacecpp11crayondplyrfansifarverforcatsforeachgenericsggplot2GLMMadaptiveglmnetgluegridExtragtablehavenhmsisobanditeratorsJMbayes2jomolabelinglatticelifecyclelme4magrittrMASSMatrixmatrixStatsmgcvmiceminqamitmlmunsellnleqslvnlmenloptrnnetnumDerivordinalpanparallellypillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloRcppEigenreadrrlangrpartscalesshapestatmodstringistringrsurvivaltibbletidyrtidyselecttzdbucminfutf8vctrsviridisLitevroomwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| long_data | long_data |
| Coefficient estimation in the longitudinal model | long_est |
| long_data | surv_data |
| Coefficient estimation in the survival model with longitudinal measurements. | surv_est |
| long_data | train_data |