In the R environment, set the root directory of RSCAT as the working directory.Rename the project folder without special characters, e.g., “RSCAT”. Clone or download the RSCAT project from repository.In the R environment, install the “devtools” R package.Install the RSCAT package using devtools:.In the R environment, run install.packages("RSCAT") to install RSCAT from a CRAN-like repository, or.Install the RSCAT package, you can choose one of the following two approaches:.Install FICO Xpress with the community license ().Make sure Java and R are both of 64bit architecture. Install Java SE Runtime Environment 8 64-bit ().Some useful information can be found at (). These issues are out of scope of these instructions and the best place to find answers is Dr. Google. You may experience some issues of installing and running Java and rJava, especially on Mac OS. It is not guaranteed that these instructions will work on every machine.
#INSTALL RJAVA IN R MAC MAC OS#
The following instructions have been tested on multiple Windows and Mac OS machines.
Please note that the RSCAT package depends on Java and the R library “rJava”. R functions and classes are provided as API wrappers to configure and run CAT simulations in the R environment. CAT algorithms are implemented in Java and the shadow-test MIP is modeled in FICO Xpress-Mosel. RSCAT is currently designed for dichotomous items based on the three-parameter logistic (3PL) model. The objective of RSCAT is twofold: 1) Enhancing the effectiveness of shadow-test CAT simulation 2) Contributing to the academic and scientific community for CAT research. RSCAT is an R package for the shadow-test approach to CAT. Selecting items from shadow tests guarantees the compliance of all content constraints defined by the blueprint.
As an advanced approach to computerized adaptive testing (CAT), shadow testing (van der Linden, 2005) dynamically assembles entire shadow tests as a part of selecting items throughout the testing process.
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