Item response theory for longitudinal data: population parameter estimation

In this work we propose IRT models to estimate ability distribution parameters of a population of individuals submitted to different tests along the time, having or not common items. The item parameters are considered known and several covariance structures are proposed to accommodate the possible d...

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Veröffentlicht in:	Journal of multivariate analysis 2005-07, Vol.95 (1), p.1-22
Hauptverfasser:	Andrade, Dalton F., Tavares, Heliton R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Covariance structures Distribution Estimating techniques Exact sciences and technology Linear inference, regression Logistic model Longitudinal data Longitudinal data Population parameters Logistic model Covariance structures Multivariate latent distribution Mathematical models Mathematics Multivariate analysis Multivariate latent distribution Parameter estimation Parametric inference Population parameters Probability and statistics Sciences and techniques of general use Statistics Studies Tests
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Beschreibung
Zusammenfassung:	In this work we propose IRT models to estimate ability distribution parameters of a population of individuals submitted to different tests along the time, having or not common items. The item parameters are considered known and several covariance structures are proposed to accommodate the possible dependence among the abilities of the same individual, measured at different instants. Maximum likelihood equations and some simulation results are presented.
ISSN:	0047-259X 1095-7243
DOI:	10.1016/j.jmva.2004.07.005