Abstract
The present paper investigates the application of two regression-based approaches, individual multiple regression and hierarchical linear modelling, in modelling differences in judgment formation of primary school teachers’ secondary school track recommendations. Both approaches share the same theoretical framework of judgment formation as a weighted linear information integration, but differ in their capacity to take differences in judgment formation into account. First, both approaches were applied to empirical data on teachers’ track recommendations and led to deviating conclusions on differences in judgment formation. To investigate which approach results in more reliable representation of actual differences in judgment formation, both approaches were compared based on simulated data and hierarchical linear modelling performed slightly more accurate than individual regression. Thus, hierarchical linear modelling might be considered the preferable modelling approach in research on judgments on school tracking recommendations.
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Hörstermann, T., Krolak-Schwerdt, S. (2015). Linear Modelling of Differences in Teacher Judgment Formation of School Tracking Recommendations. In: Lausen, B., Krolak-Schwerdt, S., Böhmer, M. (eds) Data Science, Learning by Latent Structures, and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44983-7_32
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DOI: https://doi.org/10.1007/978-3-662-44983-7_32
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