pmvalsampsize
Sample size for external validation of a prediction model
Installation
$ pip install pmvalsampsize
Usage
pmvalsampsize computes the minimum sample size required for the external validation of an existing multivariable prediction model using the criteria proposed by Archer (2020) and Riley (2021)
pmvalsampsize can currently be used to calculate the minimum sample size for the external validation of models with binary outcomes.
Continuous and survival (time-to-event) outcome model calculations are a work in progress.
from pmvalsampsize.pmvalsampsize import *
samplesize = pmvalsampsize(type="b", cstatistic=0.8, graph=True, lpbeta=(1.33, 1.75), prevalence=0.43, noprint=True) # change options to meet your requirements
plt.show()
summary(samplesize)
Contributing
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
License
pmvalsampsize was created by Rebecca Whittle & Joie Ensor. It is licensed under the terms of the GNU General Public License v3.0 license.
Credits
pmvalsampsize is based on the original R package pmvalsampsize developed by Joie Ensor.
pmvalsampsize was created with cookiecutter and the py-pkgs-cookiecutter template.
1 maintainer
Metadata
1 maintainer
Release files for pmvalsampsize 0.2.1
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| File | Size | Uploaded | Provenance | Actions |
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Total release size: 46.0 kB
Release files / pmvalsampsize-0.2.1.tar.gz
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