Multidimensional item response theory in R.

Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm. Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item functioning and modelling item and person covariates.

It's recommended to use the development version of this package since it is more likely to be up to date than the version on CRAN. To install this package from source:

1. Obtain recent gcc, g++, and gfortran compilers. Windows users can install the Rtools suite while Mac users will have to download the necessary tools from the Xcode suite and its related command line tools (found within Xcode's Preference Pane under Downloads/Components); most Linux distributions should already have up to date compilers (or if not they can be updated easily). Windows users should include the checkbox option of installing Rtools to their path for easier command line usage.

2. Install the devtools package (if necessary). In R, paste the following into the console:

install.packages('devtools')

3. Load the devtools package (requires version 1.4+) and install from the Github source code.

library('devtools')
install_github('philchalmers/mirt')

If the devtools approach does not work on your system, then you can download and install the repository directly.

1. Obtain recent gcc, g++, and gfortran compilers (see above instructions).

2. Install the git command line tools.

3. Open a terminal/command-line tool. The following code will download the repository code to your computer, and install the package directly using R tools (Windows users may also have to add R and git to their path)

git clone https://github.com/philchalmers/mirt
R CMD INSTALL mirt

Below are some presentation/workshop files for mirt that I have written and presented, and may be helpful in understanding the package.

• 2013 workshop in Klagenfurt, Austria, along with the Examples presented and Exercises provided
• 2012 presentation at York University, Toronto

Bug reports are always welcome and the preferred way to address these bugs is through the Github 'issues'. Feel free to submit issues or feature requests on the site, and I'll address them ASAP. Also, if you have any questions about the package, or IRT in general, then feel free to create a 'New Topic' in the mirt-package Google group. Cheers!