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Number of items: 30.

Debelak, Rudolf; Strobl, Carolin (2019). Investigating measurement invariance by means of parameter instability tests for 2PL and 3PL models. Educational and Psycological Measurement, 79(2):385-398.

Philipp, Michel; Strobl, Carolin; de la Torre, Jimmy; Zeileis, Achim (2018). On the Estimation of Standard Errors in Cognitive Diagnosis Models. Journal of Educational and Behavioral Statistics, 43(1):88-115.

Wang, Ting; Strobl, Carolin; Zeileis, Achim; Merkle, Edgar C (2018). Score-Based Tests of Differential Item Functioning via Pairwise Maximum Likelihood Estimation. Psychometrika, 83(1):132-155.

Komboz, Basil; Strobl, Carolin; Zeileis, Achim (2018). Tree-Based Global Model Tests for Polytomous Rasch Models. Educational and Psycological Measurement, 78(1):128-166.

Bollmann, Stella; Cook, Dianne; Dumas, Jasmine; Fox, John; Josse, Julie; Keyes, Oliver; Strobl, Carolin; Turner, Heather; Debelak, Rudolf (2017). Forwards Column. R Journal, 9(2):541-552.

Philipp, Michel; Rusch, Thomas; Hornik, Kurt; Strobl, Carolin (2017). Measuring the Stability of Results from Supervised Statistical Learning. Wien: Wirtschaftsuniversität Wien.

Kopf, Julia; Zeileis, Achim; Strobl, Carolin (2015). Anchor selection strategies for DIF analysis : review, assessment, and new approaches. Educational and Psycological Measurement, 75(1):22-56.

Strobl, Carolin; Kopf, Julia; Zeileis, Achim (2015). Rasch trees: a new method for detecting differential item functioning in the rasch model. Psychometrika, 80(2):289-316.

Kopf, Julia; Zeileis, A; Strobl, Carolin (2015). A framework for anchor methods and an iterative forward approach for DIF detection. Applied Psychological Measurement, 39(2):83-103.

Müller, Jörg; Wende, Beate; Strobl, Carolin; Eugster, Manuel; Gallenberger, Iris; Floren, Andreas; Steffan-Dewenter, Ingolf; Linsenmair, Karl Eduard; Weisser, Wolfgang W; Gossner, Martin M (2015). Forest management and regional tree composition drive the host preference of saproxylic beetle communities. Journal of Applied Ecology, 52(3):753-762.

Boulesteix, Anne-Laure; Janitza, Silke; Hapfelmeier, Alexander; Van Steen, Kristel; Strobl, Carolin (2015). Letter to the editor : on the term 'interaction' and related phrases in the literature on random forests. Briefings in Bioinformatics, 16(2):338-345.

Frick, Hannah; Strobl, Carolin; Zeileis, Achim (2015). Rasch Mixture Models for DIF Detection: a comparison of old and new score specifications. Educational and Psycological Measurement, 75(2):208-234.

Frick, Hannah; Strobl, Carolin; Zeileis, A (2014). To Split or to Mix? Tree vs. Mixture Models for Detecting Subgroups. In: COMPSTAT 2014 : 21st International Conference on Computational Statistics, Genf, 19 August 2014 - 22 August 2014, 378-386.

Eugster, Manuel J A; Leisch, Friedrich; Strobl, Carolin (2014). (Psycho-)analysis of benchmark experiments : a formal framework for investigating the relationship between data sets and learning algorithms. Computational Statistics & Data Analysis, 71:986-1000.

Hapfelmeier, Alexander; Hothorn, Torsten; Ulm, Kurt; Strobl, Carolin (2014). A new variable importance measure for random forests with missing data. Statistics and Computing, 24(1):21-34.

Strobl, Carolin (2014). Discussion on fifty years of classification and regression trees. International Statistical Review, 82(3):349-352.

Kopf, Julia; Augustin, Thomas; Strobl, Carolin (2014). The potential of model-based recursive partitioning in the social sciences – Revisiting Ockham's Razor. In: McArdle, John J; Ritschard, Gilbert. Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences. New York: Routledge, 75-95.

Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure (2013). An AUC-based permutation variable importance measure for random forests. BMC Bioinformatics, 14:119.

Strobl, Carolin (2013). Data Mining. In: Little, Todd D. The Oxford Handbook of Quantitative Methods, Vol. 2 Statistical Analysis. New York: Oxford University Press, Chaper 29.

Sauer, Sebastian; Strobl, Carolin; Walach, Harald; Kohls, Niko (2013). Rasch-Analyse des Freiburger Fragebogens zur Achtsamkeit. Diagnostica, 59(2):86-99.

Strobl, Carolin (2012). Das Rasch-Modell : eine verständliche Einführung für Studium und Praxis. München: Hampp.

Frick, H; Strobl, Carolin; Leisch, F; Zeileis, A (2012). Flexible Rasch Mixture Models with package psychomix. Journal of Statistical Software, 48(7):1-25.

Wickelmaier, Florian; Strobl, Carolin; Zeileis, Achim (2012). Psychoco: Psychometric computing in R. Journal of Statistical Software, 48(1):1-5.

Boulesteix, Anne-Laure; Bender, Andreas; Bermejo, Justo Lorenzo; Strobl, Carolin (2012). Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations. Briefings in Bioinformatics, 13(3):292-304.

Strobl, Carolin; Wickelmaier, F; Zeileis, A (2011). Accounting for individual differences in Bradley-Terry models by Means of recursive partitioning. Journal of Educational and Behavioral Statistics, 36(2):135-153.

Boulesteix, Anne-Laure; Bender, Andreas; Bermejo, Justo Lorenzo; Strobl, Carolin (2011). Random forest Gini importance favors SNPs with large minor allele frequency. München: Institut für Statistik der Ludwig-Maximilians-Universität.

Frick, H; Strobl, Carolin; Leisch, F; Zeileis, A (2011). psychomix - Psychometric Mixture Models: Version 0.1-1. Wien: The R Foundation for Statistical Computing.

Zeileis, A; Strobl, Carolin; Wickelmaier, F (2011). psychotools - Infrastructure for Psychometric Modeling: Version 0.1-1. Wien: The R Foundation for Statistical Computing.

Zeileis, Achim; Strobl, Carolin; Wickelmaier, Florian; Kopf, Julia (2011). psychotree - Recursive partitioning based on psychometric models: Version 0.12-1. Wien: The R Foundation for Statistical Computing.

Kopf, Julia; Augustin, Thomas; Strobl, Carolin (2010). The potential of model-based recursive partitioning in the social sciences - Revisiting Ockham's Razor. München: University of Munich - Department of Statistics.

This list was generated on Thu Jun 27 12:35:14 2019 CEST.