Provides tools for determining estimability of linear functions of regression coefficients, and 'epredict' methods that handle non-estimable cases correctly. Estimability theory is discussed in many linear-models textbooks including Chapter 3 of Monahan, JF (2008), "A Primer on Linear Models", Chapman and Hall (ISBN 978-1-4200-6201-4).
Version: | 1.5.1 |
Depends: | stats, R (≥ 4.1.0) |
Suggests: | knitr, rmarkdown |
Published: | 2024-05-12 |
DOI: | 10.32614/CRAN.package.estimability |
Author: | Russell Lenth [aut, cre, cph] |
Maintainer: | Russell Lenth <russell-lenth at uiowa.edu> |
BugReports: | https://github.com/rvlenth/estimability/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/rvlenth/estimability, https://rvlenth.github.io/estimability/ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | estimability results |
Reference manual: | estimability.pdf |
Vignettes: |
How to add estimability checking to your model's 'predict' method |
Package source: | estimability_1.5.1.tar.gz |
Windows binaries: | r-devel: estimability_1.5.1.zip, r-release: estimability_1.5.1.zip, r-oldrel: estimability_1.5.1.zip |
macOS binaries: | r-release (arm64): estimability_1.5.1.tgz, r-oldrel (arm64): estimability_1.5.1.tgz, r-release (x86_64): estimability_1.5.1.tgz, r-oldrel (x86_64): estimability_1.5.1.tgz |
Old sources: | estimability archive |
Reverse imports: | effects, emmeans, rsm |
Reverse suggests: | estimatr, fddm, fixest, GLMMadaptive, glmmTMB, LabApplStat, logistf, mmrm, robustlmm, sdmTMB, spmodel, survstan |
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