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MonteCarloSEM
View on CRAN: Click
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Download and install MonteCarloSEM package within the R console
Install from CRAN:
install.packages("MonteCarloSEM")
Install from Github:
library("remotes")
install_github("cran/MonteCarloSEM")
Install by package version:
library("remotes")
install_version("MonteCarloSEM", "0.0.8")
Attach the package and use:
library("MonteCarloSEM")
Maintained by
Fatih Orcan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-22
Latest Update: 2023-05-02
Description:
Monte Carlo simulation allows testing different conditions given to the correct structural equation models. This package runs Monte Carlo simulations under different conditions (such as sample size or normality of data). Within the package data sets can be simulated and run based on the given model.
First, continuous and normal data sets are generated based on the given model. Later Fleishman's power method (1978) is used to add non-normality if exists.
When data generation is completed (or when generated data sets are given) model test can also be run.
Please cite as "Or
How to cite:
Fatih Orcan (2020). MonteCarloSEM: Monte Carlo Data Simulation Package. R package version 0.0.8, https://cran.r-project.org/web/packages/MonteCarloSEM
Previous versions and publish date:
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Other R packages that MonteCarloSEM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the MonteCarloSEM R package
Some associated functions: MCAR.data . MNAR.data . fcors.value . fit.simulation . loading.value . sim.categoric . sim.normal . sim.skewed .
Some associated R codes: Input_fcors.R . Input_floads.R . MCAR.R . MNAR.R . run.sem.sim.R . sim_Categoric.R . sim_Normal.R . sim_Skewed.R . Full MonteCarloSEM package functions and examples
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