slim: Singular Linear Models for Longitudinal Data
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.
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.2.0), data.table (≥ 1.9.6) |
| Imports: |
stats, MASS (≥ 7.3) |
| Suggests: |
lme4 (≥ 1.1), jmcm (≥ 0.1.6.0), gee (≥ 4.13-19), ggplot2 (≥ 2.1.0), testthat (≥ 1.0.2), knitr, rmarkdown |
| Published: |
2017-05-15 |
| Author: |
Daniel Farewell [aut, cre] |
| Maintainer: |
Daniel Farewell <farewelld at cf.ac.uk> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
slim results |
Documentation:
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