about
Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional predictionAn introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.Bias in random forest variable importance measures: illustrations, sources and a solution.Multiple testing for SNP-SNP interactions.Conditional variable importance for random forests.The behaviour of random forest permutation-based variable importance measures under predictor correlation.An AUC-based permutation variable importance measure for random forestsLetter to the Editor: On the term 'interaction' and related phrases in the literature on Random Forests.Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model.Analysis of the individual and aggregate genetic contributions of previously identified serine peptidase inhibitor Kazal type 5 (SPINK5), kallikrein-related peptidase 7 (KLK7), and filaggrin (FLG) polymorphisms to eczema risk.Score-Based Tests of Differential Item Functioning via Pairwise Maximum Likelihood Estimation.Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations.Rasch Mixture Models for DIF Detection: A Comparison of Old and New Score Specifications.A Framework for Anchor Methods and an Iterative Forward Approach for DIF Detection.Anchor Selection Strategies for DIF Analysis: Review, Assessment, and New Approaches.(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithmsMeasurement and Predictors of a Negative Attitude towards Statistics among LMU StudentsForest management and regional tree composition drive the host preference of saproxylic beetle communitiesOn the Estimation of Standard Errors in Cognitive Diagnosis ModelsTree-Based Global Model Tests for Polytomous Rasch ModelsFlexible Rasch Mixture Models with PackagepsychomixPsychoco: Psychometric Computing inRAccounting for Individual Differences in Bradley-Terry Models by Means of Recursive PartitioningWissen Frauen weniger oder nur das Falsche? Ein statistisches Modell für unterschiedliche Aufgaben-Schwierigkeiten in TeilstichprobenParty on!Unbiased split selection for classification trees based on the Gini Index
P50
Q24288960-A9AA9CA4-B80E-479F-8C10-66DA8A504003Q30496268-C907CA23-2CA2-4B44-88BF-A42A3D470B5FQ33270401-CDD836BB-CEDB-43FF-BB6F-4B3CBD51FF01Q33313029-C54DBCCB-BED8-4B70-AD4C-2A8D1BDDAB4FQ33351067-A03C5239-E989-42E8-A5FC-643E58330537Q33534890-9CD98CA3-E123-4FB9-81DF-6DCEB8102E8AQ34656816-83F19B9A-10B1-4992-9F4B-67E83526DA3AQ38203857-B1870219-97B2-49CE-A04C-23AD68B919C6Q45112776-1BBEC086-6266-4554-8864-521137623D7DQ46386883-DE902DBA-3BED-4C61-B2AC-3C1A7E864819Q47575923-B002B9DA-CFFE-43D5-A020-F31E3EBCF058Q51532942-C54AB513-4458-4EC9-8011-72E407EDA56AQ54943597-4D18EA55-0A63-40F4-B311-0331476B545DQ55004681-B9C73D38-2952-410E-A938-8BD9D57B52A7Q55335180-45D4FF77-6313-4C26-87B7-848DD2D020B7Q57066244-557181B7-80F0-4F8D-ACD1-90C9214D82E5Q57066355-ED645662-7CBC-4216-B48D-FD3DF01C5BF4Q57201148-EB7201DD-8118-4AA9-914C-5DA49577AC9AQ57263753-113A4ED2-3E68-4C1D-8998-77A8947AAE6EQ57263764-FEEC5F15-DEDC-40BB-9051-C357C26273D5Q57263805-2DBF308F-4142-44E0-9221-0A281BC18658Q57263806-C124B6AC-A538-412A-8C80-84C20B8D53BFQ57263810-02E0ADAB-510F-4C39-AD88-B34BC55364D3Q57263820-CC845336-737E-49CA-A51B-C93918D64F7DQ62645644-C70FD305-F93C-45FF-A5BF-76F0A6E5EE5FQ63071608-5A16F72F-8F13-4002-868D-E197B7A8C729
P50
name
Carolin Strobl
@en
Carolin Strobl
@nl
type
label
Carolin Strobl
@en
Carolin Strobl
@nl
prefLabel
Carolin Strobl
@en
Carolin Strobl
@nl