Title: dexterMST: An R Package to Manage and Analyze Data from Multistage Tests Authors: Ivailo Partchev, Timo Bechger, Jesse Koops Affiliation: CITO Abstract: Multistage tests (MST) are arguably the most promising way to introduce interactivity into summative assessment. dexterMST is, to our knowledge, the only package that offers the possibility to calibrate item parameters from MST using conditional maximum likelihood (CML) estimation (Zwitser and Maris 2015). It includes functions for importing and managing test data, assessing and improving the quality of data through basic test and item analysis, and fitting an IRT model, all adapted to the peculiarities of MST designs. dexterMST accepts designs with any number of stages and modules, including combinations of linear and MST. We explain the principles underlying its design, and we share some experiences while using it in practice.