pmsampsize
Sample size for development of a prediction model.
Installation
$ pip install pmsampsize
Usage
pmsampsize computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018). 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) 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.
from pmsampsize.pmsampsize import *
samplesize = pmsampsize(type="b", cstatistic=0.89, parameters=24, prevalence=0.174) # change options to meet your requirements
License
pmsampsize was created by Rebecca Whittle & Joie Ensor. It is licensed under the terms of the GNU General Public License v3.0 license.
Credits
pmsampsize is based on the original R package pmsampsize developed by Joie Ensor.
pmsampsize was created with cookiecutter and the py-pkgs-cookiecutter template.
1 maintainer
Metadata
1 maintainer
Release files for pmsampsize 0.1.0
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