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multisite.accuracy  

Estimation of Accuracy in Multisite Machine-Learning Models
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/multisite.accuracy")

Install by package version:
library("remotes")
install_version("multisite.accuracy", "1.3")



Attach the package and use:
library("multisite.accuracy")
Maintained by
Joaquim Radua
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-28
Latest Update: 2024-07-31
Description:
The effects of the site may severely bias the accuracy of a multisite machine-learning model, even if the analysts removed them when fitting the model in the 'training set' and applying the model in the 'test set' (Solanes et al., Neuroimage 2023, 265:119800). This simple R package estimates the accuracy of a multisite machine-learning model unbiasedly, as described in (Solanes et al., Psychiatry Research: Neuroimaging 2021, 314:111313). It currently supports the estimation of sensitivity, specificity, balanced accuracy (for binary or multinomial variables), the area under the curve, correlation, mean squarer error, and hazard ratio for binomial, multinomial, gaussian, and survival (time-to-event) outcomes.
How to cite:
Joaquim Radua (2021). multisite.accuracy: Estimation of Accuracy in Multisite Machine-Learning Models. R package version 1.3, https://cran.r-project.org/web/packages/multisite.accuracy. Accessed 04 Jun. 2026.
Previous versions and publish date:
1.0 (2021-05-28 09:40), 1.1 (2022-05-05 14:50), 1.2 (2023-04-18 21:20)
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Complete documentation for multisite.accuracy
Functions, R codes and Examples using the multisite.accuracy R package
Some associated functions: multisite.accuracy . 
Some associated R codes: source.R .  Full multisite.accuracy package functions and examples
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