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mpower  

Power Analysis via Monte Carlo Simulation for Correlated Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mpower", "0.1.0")



Attach the package and use:
library("mpower")
Maintained by
Phuc H. Nguyen
[Scholar Profile | Author Map]
First Published: 2022-09-21
Latest Update: 2022-09-21
Description:
A flexible framework for power analysis using Monte Carlo simulation for settings in which considerations of the correlations between predictors are important. Users can set up a data generative model that preserves dependence structures among predictors given existing data (continuous, binary, or ordinal). Users can also generate power curves to assess the trade-offs between sample size, effect size, and power of a design. This package includes several statistical models common in environmental mixtures studies. For more details and tutorials, see Nguyen et al. (2022) .
How to cite:
Phuc H. Nguyen (2022). mpower: Power Analysis via Monte Carlo Simulation for Correlated Data. R package version 0.1.0, https://cran.r-project.org/web/packages/mpower. Accessed 06 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited mpower R package
View mpower citation profile
Other R packages that mpower depends, imports, suggests or enhances
Complete documentation for mpower
Functions, R codes and Examples using the mpower R package
Some associated functions: InferenceModel . MixtureModel . OutcomeModel . bkmr_wrapper . bma_wrapper . bws_wrapper . cor2partial . cvine . estimate_snr . fin_wrapper . fit . genx . geny . glm_wrapper . mplot . mpower . nhanes1518 . partial . plot_summary . qgcomp_lin_wrapper . qmultinom . rsq2snr . scale_f . scale_sigma . set_value . sim_curve . sim_power . summary . 
Some associated R codes: cvine.R . data.R . helpers.R . inference.R . mixture.R . mpower.R . outcome.R . sim.R . size.R .  Full mpower package functions and examples
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