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ORCIDSabine Krolak-Schwerdt
Person information
- affiliation: University of Luxembourg
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2010 – 2019
- 2015
[e1]Berthold Lausen
, Sabine Krolak-Schwerdt, Matthias Böhmer:
Data Science, Learning by Latent Structures, and Knowledge Discovery [revised versions of selected papers presented during the European Conference on Data Analysis (ECDA 2013), Luxembourg, July 2013]. Studies in Classification, Data Analysis, and Knowledge Organization, Springer 2015, ISBN 978-3-662-44982-0 [contents]- 2013
- [c7]Thomas Hörstermann, Sabine Krolak-Schwerdt:
Linear Modelling of Differences in Teacher Judgment Formation of School Tracking Recommendations. ECDA 2013: 367-377 - 2012
- [c6]Florian Klapproth, Sabine Krolak-Schwerdt, Thomas Hörstermann, Romain Martin:
Predictive Validity of Tracking Decisions: Application of a New Validation Criterion. GfKl 2012: 61-69 - [c5]Thomas Hörstermann, Sabine Krolak-Schwerdt:
Comparing Regression Approaches in Modelling Compensatory and Noncompensatory Judgment Formation. GfKl 2012: 379-387 - 2010
- [c4]Thomas Hörstermann, Sabine Krolak-Schwerdt:
Teachers' Typology of Student Categories: A Cluster Analytic Study. GfKl 2010: 547-555
2000 – 2009
- 2008
- [c3]Sabine Krolak-Schwerdt:
Strategies of Model Construction for the Analysis of Judgment Data. GfKl 2008: 21-32 - 2005
- [c2]Sabine Krolak-Schwerdt, Michael Wiedenbeck:
The Recovery Performance of Two-mode Clustering Methods: Monte Carlo Experiment. GfKl 2005: 190-197 - [p1]Sabine Krolak-Schwerdt:
Three-Way Multidimensional Scaling: Formal Properties and Relationships Between Scaling Methods. Data Analysis and Decision Support 2005: 82-90 - 2004
- [c1]Sabine Krolak-Schwerdt:
A Three-way Multidimensional Scaling Approach to the Analysis of Judgments About Persons. GfKl 2004: 264-271
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