Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
%lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models | Olsbjerg | Journal of Statistical Software
Authors: Maja Olsbjerg, Karl Bang Christensen
Title: %lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models
Abstract: Item response theory models are often applied when a number items are used to measure a unidimensional latent variable. Originally proposed and used within educational research, they are also used when focus is on physical functioning or psychological wellbeing. Modern applications often need more general models, typically models for multidimensional latent variables or longitudinal models for repeated measurements. This paper describes a SAS macro that fits two-dimensional polytomous Rasch models using a specification of the model that is sufficiently flexible to accommodate longitudinal Rasch models. The macro estimates item parameters using marginal maximum likelihood estimation. A graphical presentation of item characteristic curves is included.

Page views:: 600. Submitted: 2013-10-29. Published: 2015-10-07.
Paper: %lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models     Download PDF (Downloads: 628)
Supplements:
lrasch_mml.sas: SAS source code Download (Downloads: 64; 27KB)
v67c02.sas: SAS replication code Download (Downloads: 51; 2KB)
scqol.sas7bdat: Replication data Download (Downloads: 54; 25KB)

DOI: 10.18637/jss.v067.c02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.