Estimating Item Parameters in Multistage Designs With the tmt Package in R

Abstract: Various likelihood-based methods are available for the parameter estimation of item response theory models (IRT), leading to comparable parameter estimates. Considering multistage testing (MST) designs, Glas (1988; https://doi.org/10.2307/1164950) stated that the conditional maximum likelihood (CML) method in its original formulation leads to severely biased parameter estimates. A modified CML estimation method for MST designs proposed by Zwitser and Maris (2015; https://doi.org/10.1007/s11336-013-9369-6) finally provides asymptotically unbiased item parameter estimates. Steinfeld and Robitzsch (2021b; https://doi.org/10.31234/osf.io/ew27f) complemented this method to MST designs with probabilistic routing strategies. For both proposed modifications additional software solutions are required since design-specific information must be incorporated into the estimation process. An R package that has implemented both modifications is "tmt". In this article, first, the proposed solutions.... https://qcmb.psychopen.eu/index.php/qcmb/article/view/10087

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Estimating Item Parameters in Multistage Designs With the tmt Package in R ; volume:3 ; day:06 ; month:11 ; year:2023 ; Quantitative and computational methods in behavioral sciences ; 3 (06.11.2023)

Contributors, Places and Time

• Creator: Steinfeld, Jan ; Robitzsch, Alexander

Further information

• DOI: 10.5964/qcmb.10087
• URN: urn:nbn:de:101:1-2023111014090440629299
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 10:47 AM CEST