%lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models

Research output: Contribution to journalJournal articleResearchpeer-review

Item response theory models are often applied when a number items are used to measurea unidimensional latent variable. Originally proposed and used within educationalresearch, they are also used when focus is on physical functioning or psychological wellbeing.Modern applications often need more general models, typically models for multidimensionallatent variables or longitudinal models for repeated measurements. This paperdescribes a SAS macro that fits two-dimensional polytomous Rasch models using a specifi-cation of the model that is sufficiently flexible to accommodate longitudinal Rasch models.The macro estimates item parameters using marginal maximum likelihood estimation. Agraphical presentation of item characteristic curves is included.
Original languageEnglish
JournalJournal of Statistical Software
Issue numberCode Snippet 2
Pages (from-to)1-24
Number of pages24
Publication statusPublished - 7 Oct 2015

    Research areas

  • polytomous Rasch model, longitudinal Rasch model, marginal maximum likelihood (MML) estimation, item parameter drift, response dependence, SAS macro

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