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Computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018) <doi:10.1002/sim.7992>. pmsampsize can be used to calculate the minimum sample size for the development of models with continuous, binary or survival (time-to-event) outcomes. Riley et al. (2018) <doi:10.1002/sim.7992> lay out a series of criteria the sample size should meet. These aim to minimise the overfitting and to ensure precise estimation of key parameters in the prediction model.
| Version: | 1.1.3 |
| Depends: | R (≥ 2.1) |
| Suggests: | stats |
| Published: | 2023-12-06 |
| Author: | Joie Ensor [aut, cre] |
| Maintainer: | Joie Ensor <j.ensor at bham.ac.uk> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | pmsampsize results |
| Reference manual: | pmsampsize.pdf |
| Package source: | pmsampsize_1.1.3.tar.gz |
| Windows binaries: | r-devel: pmsampsize_1.1.3.zip, r-release: pmsampsize_1.1.3.zip, r-oldrel: pmsampsize_1.1.3.zip |
| macOS binaries: | r-release (arm64): pmsampsize_1.1.3.tgz, r-oldrel (arm64): pmsampsize_1.1.3.tgz, r-release (x86_64): pmsampsize_1.1.3.tgz, r-oldrel (x86_64): pmsampsize_1.1.3.tgz |
| Old sources: | pmsampsize archive |
| Reverse imports: | predictNMB |
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These binaries (installable software) and packages are in development.
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