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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 |
| Depends: | stats, R (≥ 4.3.0) |
| Suggests: | knitr, rmarkdown |
| Published: | 2024-02-20 |
| Author: | Russell Lenth [aut, cre, cph] |
| Maintainer: | Russell Lenth <russell-lenth at uiowa.edu> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | estimability results |
| Reference manual: | estimability.pdf |
| Vignettes: |
Adding estimability checking to to your predict method |
| Package source: | estimability_1.5.tar.gz |
| Windows binaries: | r-devel: estimability_1.5.zip, r-release: estimability_1.5.zip, r-oldrel: estimability_1.5.zip |
| macOS binaries: | r-release (arm64): estimability_1.5.tgz, r-oldrel (arm64): estimability_1.5.tgz, r-release (x86_64): estimability_1.5.tgz, r-oldrel (x86_64): estimability_1.5.tgz |
| Old sources: | estimability archive |
| Reverse imports: | effects, emmeans, rsm |
| Reverse suggests: | estimatr, fixest, GLMMadaptive, glmmTMB, LabApplStat, logistf, mmrm, robustlmm, sdmTMB, survstan |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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