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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>.
Getting started
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Package details |
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| Author | Jiacong Du [aut] (<https://orcid.org/0000-0002-7768-9083>), Howard Baik [cre] (<https://orcid.org/0009-0000-8942-1618>) |
| Maintainer | Howard Baik <howard.baik@yale.edu> |
| License | GPL (>= 3) |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
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