![[höher]](/style/images/multi_up.png)
Eine Ebene höherGruppiert nach:
Dokumententyp
| Veröffentlichungsdatum
Anzahl der Publikationen: 45
Monographie
Strobl, Carolin
(2010):
Das Rasch-Modell. Eine verständliche Einführung für Studium und Praxis.
Mering: Hampp Verlag.
Zeitschriftenartikel
Schneider, Lennart; Strobl, Carolin; Zeileis, Achim und Debelak, Rudolf
(2022):
An R toolbox for score-based measurement invariance tests in IRT models.
In: Behavior Research Methods, Bd. 54, Nr. 5: S. 2101-2113
Komboz, Basil; Strobl, Carolin und Zeileis, Achim
(2018):
Tree-Based Global Model Tests for Polytomous Rasch Models.
In: Educational and Psychological Measurement, Bd. 78, Nr. 1: S. 128-166
Kopf, Julia; Zeileis, Achim und Strobl, Carolin
(2015):
Anchor Selection Strategies for DIF Analysis. Review, Assessment, and New Approaches.
In: Educational and Psychological Measurement, Bd. 75, Nr. 1: S. 22-56
[PDF, 815kB]
Kopf, Julia; Zeileis, Achim und Strobl, Carolin
(2015):
A Framework for Anchor Methods and an Iterative Forward Approach for DIF Detection.
In: Applied Psychological Measurement, Bd. 39, Nr. 2: S. 83-103
[PDF, 408kB]
Hapfelmeier, Alexander; Hothorn, Torsten; Ulm, Kurt und Strobl, Carolin
(2014):
A New Variable Importance Measure for Random Forests with Missing Data.
In: Statistics and Computing, Bd. 24, Nr. 1: S. 21-34
Janitza, Silke; Strobl, Carolin und Boulesteix, Anne-Laure
(2013):
An AUC-based permutation variable importance measure for random forests.
In: BMC Bioinformatics
14:119
[PDF, 296kB]
Strobl, Carolin; Kopf, Julia und Zeileis, Achim
(2013):
Rasch trees: A New Method for Detecting Differential Item Functioning in the Rasch Model.
In: Psychometrika: S. 1-28
Strobl, Carolin; Wickelmaier, Florian und Zeileis, Achim
(2011):
Accounting for individual differences in Bradley-Terry models by means of recursive partitioning.
In: Journal of Educational and Behavioral Statistics, Bd. 36, Nr. 2: S. 135-153
[PDF, 269kB]
Nicodemus, Kristin; Malley, James; Strobl, Carolin und Ziegler, Andreas
(2010):
The behaviour of random forest permutation-based variable importance measures under predictor correlation.
In: BMC Bioinformatics: S. 11-110
Nicodemus, Kristin K.; Malley, James D.; Strobl, Carolin und Ziegler, Andreas
(2010):
The behaviour of random forest permutation-based variable importance measures under predictor correlation.
In: BMC Bioinformatics
11:110
[PDF, 663kB]
Boulesteix, Anne-Laure und Strobl, Carolin
(2009):
Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction.
In: BMC Medical Research Methodology
9:85
[PDF, 377kB]
Boulesteix, Anne-Laure und Strobl, Carolin
(2009):
Optimal classifier selection and negative bias in error rate estimation: An empirical study on high-dimensional prediction.
In: BMC Medical Research Methodology, Bd. 9, Nr. 85
Strobl, Carolin und Augustin, Thomas
(2009):
Adaptive selection of extra cutpoints - an approach towards reconciling robustness and interpretability in classification trees.
In: Journal of Statistical Theory and Practice, Bd. 3, Nr. 1: S. 119-135
Strobl, Carolin; Hothorn, Torsten und Zeileis, Achim
(2009):
Party on! A new, conditional variable importance measure available in the party package.
In: The R Journal, Bd. 1, Nr. 2: S. 14-17
Strobl, Carolin; Malley, James und Tutz, Gerhard
(2009):
An introduction to recursive partitioning: Rationale, application and characteristics of classification and regression trees, bagging and random forests.
In: Psychological Methods, Bd. 14, Nr. 4: S. 323-348
Strobl, Carolin; Boulesteix, Anne-Laure; Kneib, Thomas; Augustin, Thomas und Zeileis, Achim
(2008):
Conditional variable importance for random forests.
In: BMC Bioinformatics
9:307
[PDF, 396kB]
Strobl, Carolin; Boulesteix, Anne-Laure; Zeileis, Achim und Hothorn, Torsten
(2007):
Bias in random forest variable importance measures: Illustrations, sources and a solution.
In: BMC Bioinformatics
8:25
[PDF, 368kB]
Paper
Abou El-Komboz, Basil; Zeileis, Achim und Strobl, Carolin
(16. Januar 2014):
Detecting Differential Item and Step Functioning with Rating Scale and Partial Credit Trees.
Department of Statistics: Technical Reports, Nr. 152
[PDF, 548kB]
Kopf, Julia; Zeileis, Achim und Strobl, Carolin
(24. November 2013):
Anchor selection strategies for DIF analysis: Review, assessment, and new approaches.
Department of Statistics: Technical Reports, Nr. 150
[PDF, 497kB]
Kopf, Julia; Zeileis, Achim und Strobl, Carolin
(13. März 2013):
Anchor methods for DIF detection: A comparison of the iterative forward, backward, constant and all-other anchor class.
Department of Statistics: Technical Reports, Nr. 141
[PDF, 549kB]
Janitza, Silke; Strobl, Carolin und Boulesteix, Anne-Laure
(November 2012):
An AUC-based Permutation Variable Importance Measure for Random Forests.
Department of Statistics: Technical Reports, Nr. 130
[PDF, 470kB]
Boulesteix, Anne-Laure; Bender, Andreas; Lorenzo Bermejo, Justo und Strobl, Carolin
(2. Mai 2011):
Random forest Gini importance favors SNPs with large minor allele frequency.
Department of Statistics: Technical Reports, Nr. 106
Briefings in Bioinformatics, 13
[PDF, 962kB]
Eugster, Manuel J. A.; Leisch, Friedrich und Strobl, Carolin
(9. März 2010):
(Psycho-)Analysis of Benchmark Experiments. A Formal Framework for Investigating the Relationship between Data Sets and Learning Algorithms.
Department of Statistics: Technical Reports, Nr. 78
[PDF, 785kB]
Rieger, Anna; Hothorn, Torsten und Strobl, Carolin
(2010):
Random Forests with Missing Values in the Covariates.
Department of Statistics: Technical Reports, Nr. 79
[PDF, 394kB]
Kopf, Julia; Augustin, Thomas und Strobl, Carolin
(2010):
The potential of model-based recursive partitioning in the social sciences - Revisiting Ockham's Razor.
Department of Statistics: Technical Reports, Nr. 88
[PDF, 661kB]
Strobl, Carolin; Kopf, Julia und Zeileis, Achim
(2010):
A new method for detecting differential item functioning in the Rasch model.
Department of Statistics: Technical Reports, Nr. 92
[PDF, 407kB]
Boulesteix, Anne-Laure und Strobl, Carolin
(8. Mai 2009):
Optimal classifier selection and negative bias in error rate estimation: An empirical study on high-dimensional prediction.
Department of Statistics: Technical Reports, Nr. 58
BMC Medical Research Methodology (accepted for publication)
[PDF, 321kB]
Strobl, Carolin; Wickelmaier, Florian und Zeileis, Achim
(April 2009):
Accounting for Individual Differences in Bradley-Terry Models by Means of Recursive Partitioning.
Department of Statistics: Technical Reports, Nr. 54
[PDF, 536kB]
Strobl, Carolin; Malley, James und Tutz, Gerhard
(April 2009):
An Introduction to Recursive Partitioning: Rationale, Application and Characteristics of Classification and Regression Trees, Bagging and Random Forests.
Department of Statistics: Technical Reports, Nr. 55
[PDF, 974kB]
Strobl, Carolin; Hothorn, Torsten und Zeileis, Achim
(11. Februar 2009):
Party on! A New, Conditional Variable Importance Measure for Random Forests Available in the party Package.
Department of Statistics: Technical Reports, Nr. 50
[PDF, 274kB]
Oppel, Steffen; Strobl, Carolin und Huettmann, Falk
(2009):
Alternative methods to quantify variable importance in ecology.
Department of Statistics: Technical Reports, Nr. 65
[PDF, 161kB]
Strobl, Carolin; Boulesteix, Anne-Laure; Kneib, Thomas; Augustin, Thomas und Zeileis, Achim
(28. März 2008):
Conditional Variable Importance for Random Forests.
Department of Statistics: Technical Reports, Nr. 23
[PDF, 394kB]
Strobl, Carolin und Zeileis, Achim
(30. Januar 2008):
Danger: High Power! – Exploring the Statistical Properties of a Test for Random Forest Variable Importance.
Department of Statistics: Technical Reports, Nr. 17
[PDF, 323kB]
Boulesteix, Anne-Laure; Strobl, Carolin; Augustin, Thomas und Daumer, Martin
(2007):
Evaluating microarray-based classifiers: an overview.
Department of Statistics: Technical Reports, Nr. 5
[PDF, 422kB]
Boulesteix, Anne-Laure; Strobl, Carolin; Weidinger, S.; Wichmann, Heinz-Erich und Wagenpfeil, S.
(2007):
Multiple testing for SNP-SNP interactions.
Department of Statistics: Technical Reports, Nr. 4
[PDF, 928kB]
Strobl, Carolin; Boulesteix, Anne-Laure; Zeileis, Achim und Hothorn, Torsten
(2006):
Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution.
Sonderforschungsbereich 386, Discussion Paper 490
[PDF, 574kB]
Boulesteix, Anne-Laure und Strobl, Carolin
(2006):
Maximally selected chi-square statistics and umbrella orderings.
Sonderforschungsbereich 386, Discussion Paper 476
[PDF, 272kB]
Strobl, Carolin
(2005):
Variable Selection Bias in Classification Trees Based on Imprecise Probabilities.
Sonderforschungsbereich 386, Discussion Paper 419
[PDF, 325kB]
Strobl, Carolin; Boulesteix, Anne-Laure und Augustin, Thomas
(2005):
Unbiased split selection for classification trees based on the Gini Index.
Sonderforschungsbereich 386, Discussion Paper 464
[PDF, 237kB]
Strobl, Carolin
(2005):
Statistical Sources of Variable Selection Bias in Classification Tree Algorithms Based on the Gini Index.
Sonderforschungsbereich 386, Discussion Paper 420
[PDF, 196kB]
Buchbeitrag
Kopf, Julia; Augustin, Thomas und Strobl, Carolin
(2013):
The potential of Model-based recursive partitioning in the social sciences. Revisiting Ockham's Razor.
In: McArdle, John J. und Ritschard, Gilbert (Hrsg.):
Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences. New York: Routledge, Taylor & Francis Group. S. 75-95
Strobl, Carolin; Kopf, Julia und Zeileis, Achim
(2010):
Wissen Frauen weniger oder nur das Falsche? Ein statistisches Modell für unterschiedliche Aufgaben-Schwierigkeiten in Teilstichproben.
In: Trepte, Sabine und Verbeet, Markus (Hrsg.):
Allgemeinbildung in Deutschland - Erkenntnisse aus dem SPIEGEL-Studentenpisa. Wiesbaden: Springer VS. S. 255-272
Strobl, Carolin; Dittrich, Christian; Seiler, Christian; Hackensperger, Sandra und Leisch, Friedrich
(2010):
Measurement and predictors of a negative attitude towards statistics among LMU students.
In: Kneib, Thomas (Hrsg.):
Statistical Modelling and Regression Structures - Festschrift in Honour of Ludwig Fahrmeir. Heidelberg: Physica-Verlag. S. 217-230
Tutz, Gerhard und Strobl, Carolin
(2010):
Generalisierte lineare Modelle.
In: Schmitz, Bernhard und Holling, Heinz (Hrsg.):
Handbuch der psychologischen Methoden und Evaluation. Göttingen: Hogrefe Verlag. S. 461-471