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| Autoren | Aßmann, Christian; Carstensen, Claus H.; Gaasch, Christoph; Pohl, Steffi |
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| Institution | Leibniz-Institut für Bildungsverläufe; Nationales Bildungspanel |
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| Titel | Estimation of plausible values using background variables with missing values. A data augmented MCMC approach. |
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| URL | https://www.neps-data.de/Portals/0/Working Papers/WP_XXXVIII.pdf |
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| Erscheinungsjahr | 2014 |
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| Seitenzahl | 15 S. |
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| Verlag | Bamberg: Leibniz Institute for Educational Trajectories (LIfBi) |
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| Reihe | NEPS working papers. Band 38 |
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| Dokumenttyp | Monographie; Graue Literatur; online |
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| Beigaben | Literaturangaben, Abbildungen, Tabellen, Anhang |
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| Sprache | englisch |
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| Forschungsschwerpunkt | Bildungspanel (NEPS) |
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| Schlagwörter | Kompetenzentwicklung; Item-Response-Theorie; Datenanalyse; Markowsche Kette; Stichprobe; Validität; Mathematische Kompetenz; Schuljahr 05; Schüler |
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| Abstract | The National Educational Panel Study (NEPS) provides data on the development of competencies across the whole life span to educational researchers and politicians. Plausible values as a measure of individual competence are estimated by explicitly including background variables capturing individual characteristics into the corresponding Item Response Theory (IRT) models. Despite tremendous efforts in field work, missing values in the background variables can occur. Adequate estimation routines are needed to reflect the uncertainty stemming from missing values in the background variables in the estimation of plausible values. To achieve this, we propose to adapt an estimation strategy based on Markov Chain Monte Carlo (MCMC) techniques that simultaneously addresses missing values in background variables in the estimation of plausible values for the competence scores. The resulting hybrid sampling scheme establishes a one-step approach for the estimation of plausible values using IRT models that incorporate background variables with missing values. In a simulation study allowing to control the mechanism causing missing values, we evaluate the validity of our approach with respect to statistical accuracy. The results show that the proposed approach is capable to recover the true regression parameters describing the relationship between latent competence scores and background variables. The approach is illustrated on an example using data from the NEPS on mathematical competencies of fifth grade students. (Orig.). |
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| Förderkennzeichen | 01GJ0888 |
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