Paper

Kopf, Julia and Zeileis, Achim and Strobl, Carolin (2013): Anchor methods for DIF detection: A comparison of the iterative forward, backward, constant and all-other anchor class. Department of Statistics: Technical Reports, No.141

Janitza, Silke and Strobl, Carolin and Boulesteix, Anne-Laure (2012): An AUC-based Permutation Variable Importance Measure for Random Forests. Department of Statistics: Technical Reports, No.130

Boulesteix, Anne-Laure and Bender, Andreas and Lorenzo Bermejo, Justo and Strobl, Carolin (2011): Random forest Gini importance favors SNPs with large minor allele frequency. Department of Statistics: Technical Reports, No.106

Eugster, Manuel J. A. and Leisch, Friedrich and Strobl, Carolin (2010): (Psycho-)Analysis of Benchmark Experiments. A Formal Framework for Investigating the Relationship between Data Sets and Learning Algorithms. Department of Statistics: Technical Reports, No.78

Rieger, Anna and Hothorn, Torsten and Strobl, Carolin (2010): Random Forests with Missing Values in the Covariates. Department of Statistics: Technical Reports, No.79

Strobl, Carolin and Kopf, Julia and Zeileis, Achim (2010): A new method for detecting differential item functioning in the Rasch model. Department of Statistics: Technical Reports, No.92

Kopf, Julia and Augustin, Thomas and Strobl, Carolin (2010): The potential of model-based recursive partitioning in the social sciences - Revisiting Ockham's Razor. Department of Statistics: Technical Reports, No.88

Boulesteix, Anne-Laure and Strobl, Carolin (2009): Optimal classifier selection and negative bias in error rate estimation: An empirical study on high-dimensional prediction. Department of Statistics: Technical Reports, No.58

Strobl, Carolin and Wickelmaier, Florian and Zeileis, Achim (2009): Accounting for Individual Differences in Bradley-Terry Models by Means of Recursive Partitioning. Department of Statistics: Technical Reports, No.54

Strobl, Carolin and Malley, James and Tutz, Gerhard (2009): An Introduction to Recursive Partitioning: Rationale, Application and Characteristics of Classification and Regression Trees, Bagging and Random Forests. Department of Statistics: Technical Reports, No.55

Strobl, Carolin and Hothorn, Torsten and Zeileis, Achim (2009): Party on! A New, Conditional Variable Importance Measure for Random Forests Available in the party Package. Department of Statistics: Technical Reports, No.50

Oppel, Steffen and Strobl, Carolin and Huettmann, Falk (2009): Alternative methods to quantify variable importance in ecology. Department of Statistics: Technical Reports, No.65

Strobl, Carolin and Boulesteix, Anne-Laure and Kneib, Thomas and Augustin, Thomas and Zeileis, Achim (2008): Conditional Variable Importance for Random Forests. Department of Statistics: Technical Reports, No.23

Strobl, Carolin and Zeileis, Achim (2008): Danger: High Power! – Exploring the Statistical Properties of a Test for Random Forest Variable Importance. Department of Statistics: Technical Reports, No.17

Boulesteix, Anne-Laure and Strobl, Carolin and Weidinger, S. and Wichmann, H. E. and Wagenpfeil, S. (2007): Multiple testing for SNP-SNP interactions. Department of Statistics: Technical Reports, No.4

Boulesteix, Anne-Laure and Strobl, Carolin and Augustin, Thomas and Daumer, Martin (2007): Evaluating microarray-based classifiers: an overview. Department of Statistics: Technical Reports, No.5

Boulesteix, Anne-Laure and Strobl, Carolin (2006): Maximally selected chi-square statistics and umbrella orderings. Collaborative Research Center 386, Discussion Paper 476

Strobl, Carolin and Boulesteix, Anne-Laure and Zeileis, Achim and Hothorn, Torsten (2006): Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution. Collaborative Research Center 386, Discussion Paper 490

Strobl, Carolin (2005): Variable Selection Bias in Classification Trees Based on Imprecise Probabilities. Collaborative Research Center 386, Discussion Paper 419

Strobl, Carolin (2005): Statistical Sources of Variable Selection Bias in Classification Tree Algorithms Based on the Gini Index. Collaborative Research Center 386, Discussion Paper 420

Strobl, Carolin and Boulesteix, Anne-Laure and Augustin, Thomas (2005): Unbiased split selection for classification trees based on the Gini Index. Collaborative Research Center 386, Discussion Paper 464