pmsampsize: Calculates the Minimum Sample Size Required for Developing a Multivariable Prediction Model

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:	1.1.2
Depends:	R (≥ 2.1)
Suggests:	stats
Published:	2022-02-12
Author:	Joie Ensor [aut, cre], Emma C. Martin [aut], Richard D. Riley [aut]
Maintainer:	Joie Ensor <j.ensor at keele.ac.uk>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	pmsampsize results

Documentation:

Reference manual:

pmsampsize.pdf

Downloads:

Package source:	pmsampsize_1.1.2.tar.gz
Windows binaries:	r-devel: pmsampsize_1.1.2.zip, r-release: pmsampsize_1.1.2.zip, r-oldrel: pmsampsize_1.1.2.zip
macOS binaries:	r-release (arm64): pmsampsize_1.1.2.tgz, r-oldrel (arm64): pmsampsize_1.1.2.tgz, r-release (x86_64): pmsampsize_1.1.2.tgz, r-oldrel (x86_64): pmsampsize_1.1.2.tgz
Old sources:	pmsampsize archive

Reverse dependencies:

Reverse imports:

predictNMB

Linking:

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