sampsizeval: Sample Size for Validation of Risk Models with Binary Outcomes

Estimation of the required sample size to validate a risk model for binary outcomes, based on the sample size equations proposed by Pavlou et al. (2021) <doi:10.1177/09622802211007522>. For precision-based sample size calculations, the user is required to enter the anticipated values of the C-statistic and outcome prevalence, which can be obtained from a previous study. The user also needs to specify the required precision (standard error) for the C-statistic, the calibration slope and the calibration in the large. The calculations are valid under the assumption of marginal normality for the distribution of the linear predictor.

Version: 1.0.0.0
Imports: stats, sn, pracma, dplyr, plyr
Suggests: testthat (≥ 3.0.0)
Published: 2021-05-28
Author: Menelaos Pavlou ORCID iD [aut, cre]
Maintainer: Menelaos Pavlou <m.pavlou at ucl.ac.uk>
BugReports: https://github.com/mpavlou/sampsizeval/issues
License: MIT + file LICENSE
URL: https://github.com/mpavlou/sampsizeval
NeedsCompilation: no
Materials: README
CRAN checks: sampsizeval results

Documentation:

Reference manual: sampsizeval.pdf

Downloads:

Package source: sampsizeval_1.0.0.0.tar.gz
Windows binaries: r-devel: sampsizeval_1.0.0.0.zip, r-release: sampsizeval_1.0.0.0.zip, r-oldrel: sampsizeval_1.0.0.0.zip
macOS binaries: r-release (arm64): sampsizeval_1.0.0.0.tgz, r-release (x86_64): sampsizeval_1.0.0.0.tgz, r-oldrel: sampsizeval_1.0.0.0.tgz

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