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pmsampsize  

Sample Size for Development of a Prediction Model
View on CRAN: Click here


Download and install pmsampsize package within the R console
Install from CRAN:
install.packages("pmsampsize")

Install from Github:
library("remotes")
install_github("cran/pmsampsize")

Install by package version:
library("remotes")
install_version("pmsampsize", "1.1.3")



Attach the package and use:
library("pmsampsize")
Maintained by
Joie Ensor
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-08
Latest Update: 2023-12-06
Description:
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.
How to cite:
Joie Ensor (2019). pmsampsize: Sample Size for Development of a Prediction Model. R package version 1.1.3, https://cran.r-project.org/web/packages/pmsampsize
Previous versions and publish date:
1.0.0 (2019-01-08 17:30), 1.0.1 (2019-08-02 19:10), 1.0.2 (2019-11-15 19:50), 1.0.3 (2020-07-23 23:20), 1.1.0 (2021-06-25 16:50), 1.1.1 (2021-11-22 10:50), 1.1.2 (2022-02-12 18:00)
Other packages that cited pmsampsize R package
View pmsampsize citation profile
Other R packages that pmsampsize depends, imports, suggests or enhances
Functions, R codes and Examples using the pmsampsize R package
Some associated functions: pmsampsize . 
Some associated R codes: cstat2rsq.R . pmsampsize.R . pmsampsize_bin.R . pmsampsize_cont.R . pmsampsize_errorcheck.R . pmsampsize_surv.R .  Full pmsampsize package functions and examples
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