Singular Linear Models for Longitudinal Data
Overview
Fits singular linear models to longitudinal data. Singular linear models are useful when the number, or timing, of longitudinal observations may be informative about the observations themselves. They are described in Farewell (2010) doi:10.1093/biomet/asp068, and are extensions of the linear increments model doi:10.1111/j.1467-9876.2007.00590.x to general longitudinal data.
Now Imports data.table, rather than Depends on it.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-30
- NOTE13 NOTE2026-06-09
- ERROR12 NOTE, 1 ERROR2026-06-08
- NOTE12 NOTE2026-04-25
- ERROR13 NOTE, 1 ERROR2026-03-30
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- NOTE14 NOTE2026-03-10
Documentation
- Help pages
- 14 (1 internal)includes a package overview page
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 7%
Downloads
Dependencies
Installing slim adds 1 package (1 with compiled code, 5.7 MB of source tarballs). Heaviest: data.table 5.7 MB.
Code & Tests
Datasets
People & History
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- 0.1.3Latest
- 0.1.22026-08-23 · diff ↗
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.1.12017-05-15 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 0.1.02016-11-07
- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-11-07
- Total releases
- 4 / 10 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.2.0
- Bundled data
- 7.0 KB / 2 files
- Download size
- 296 KB
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