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>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: dplyr, JMbayes2, lme4, mice, nleqslv, nlme, statmod, stats, survival, utils
Published: 2024-11-12
DOI: 10.32614/CRAN.package.CIMPLE
Author: Jiacong Du ORCID iD [aut], Howard Baik ORCID iD [cre]
Maintainer: Howard Baik <howard.baik at yale.edu>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: CIMPLE results

Documentation:

Reference manual: CIMPLE.pdf

Downloads:

Package source: CIMPLE_0.1.0.tar.gz
Windows binaries: r-devel: CIMPLE_0.1.0.zip, r-release: CIMPLE_0.1.0.zip, r-oldrel: CIMPLE_0.1.0.zip
macOS binaries: r-release (arm64): CIMPLE_0.1.0.tgz, r-oldrel (arm64): CIMPLE_0.1.0.tgz, r-release (x86_64): CIMPLE_0.1.0.tgz, r-oldrel (x86_64): CIMPLE_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=CIMPLE to link to this page.