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 of Diggle et al. (2007) <doi:10.1111/j.1467-9876.2007.00590.x> to general longitudinal data.

Version: 0.1.0
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: 2016-11-07
Author: Daniel Farewell [aut, cre]
Maintainer: Daniel Farewell <farewelld at cf.ac.uk>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: slim results

Downloads:

Reference manual: slim.pdf
Vignettes: slim: Singular Linear Models
Package source: slim_0.1.0.tar.gz
Windows binaries: r-devel: slim_0.1.0.zip, r-release: slim_0.1.0.zip, r-oldrel: slim_0.1.0.zip
OS X Mavericks binaries: r-release: slim_0.1.0.tgz, r-oldrel: slim_0.1.0.tgz

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