Other packages > Find by keyword >

MIRES  

Measurement Invariance Assessment Using Random Effects Models and Shrinkage
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("MIRES", "0.1.1")



Attach the package and use:
library("MIRES")
Maintained by
Stephen Martin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-22
Latest Update: 2025-05-04
Description:
Estimates random effect latent measurement models, wherein the loadings, residual variances, intercepts, latent means, and latent variances all vary across groups. The random effect variances of the measurement parameters are then modeled using a hierarchical inclusion model, wherein the inclusion of the variances (i.e., whether it is effectively zero or non-zero) is informed by similar parameters (of the same type, or of the same item). This additional hierarchical structure allows the evidence in favor of partial invariance to accumulate more quickly, and yields more certain decisions about measurement invariance. Martin, Williams, and Rast (2020) .
How to cite:
Stephen Martin (2021). MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage. R package version 0.1.1, https://cran.r-project.org/web/packages/MIRES. Accessed 05 Aug. 2026.
Previous versions and publish date:
0.1.0 (2021-02-22 11:40), (2026-07-09 08:09)
Other packages that cited MIRES R package
View MIRES citation profile
Other R packages that MIRES depends, imports, suggests or enhances
Complete documentation for MIRES
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

dhReg  
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency  
dcov  
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency  
noisyr  
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
kernelPSI  
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA