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Thomas Rusch
Thomas Rusch
WU Vienna (Vienna University of Economics and Business)
Verified email at wu.ac.at
Title
Cited by
Cited by
Year
Customer segmentation using unobserved heterogeneity in the perceived-value-loyalty-intentions link
A Floh, A Zauner, M Koller, T Rusch
Journal of Business Research, 0
260*
Capturing the familiness of family businesses: Development of the family influence familiness scale (FIFS)
H Frank, A Kessler, T Rusch, J Suess–Reyes, D Weismeier–Sammer
Entrepreneurship Theory and Practice 41 (5), 709-742, 2017
2502017
Goodness-of-fit assessment in multidimensional scaling and unfolding
P Mair, I Borg, T Rusch
Multivariate behavioral research 51 (6), 772-789, 2016
1482016
Linking cause assessment, corporate philanthropy, and corporate reputation
I Szőcs, BB Schlegelmilch, T Rusch, HM Shamma
Journal of the Academy of Marketing Science 44, 376-396, 2016
892016
Breaking free from the limitations of classical test theory: Developing and measuring information systems scales using item response theory
T Rusch, PB Lowry, P Mair, H Treiblmaier
Information & Management 54 (2), 189-203, 2017
872017
Measuring the stability of results from supervised statistical learning
M Philipp, T Rusch, K Hornik, C Strobl
Journal of Computational and Graphical Statistics 27 (4), 685-700, 2018
452018
Effect of Shamiri layperson-provided intervention vs study skills control intervention for depression and anxiety symptoms in adolescents in Kenya: a randomized clinical trial
TL Osborn, KE Venturo-Conerly, S Arango, E Roe, M Rodriguez, ...
JAMA psychiatry 78 (8), 829-837, 2021
422021
Model trees with topic model preprocessing: An approach for data journalism illustrated with the wikileaks afghanistan war logs
T Rusch, P Hofmarcher, R Hatzinger, K Hornik
372013
Package ‘eRm’
P Mair, R Hatzinger, MJ Maier, T Rusch, MP Mair
Vienna, Austria: R Foundation, 2016
362016
Gaining insight with recursive partitioning of generalized linear models
T Rusch, A Zeileis
Taylor & Francis, 2012
312012
IRT models with relaxed assumptions in eRm: A manual-like instruction
R Hatzinger, T Rusch
Psychology Science Quarterly 51 (1), 87, 2009
29*2009
Psychometrics with R: A review of CRAN packages for item response theory
T Rusch, P Mair, R Hatzinger
242013
Influencing elections with statistics: Targeting voters with logistic regression trees
T Rusch, I Lee, K Hornik, W Jank, A Zeileis
The Annals of Applied Statistics, 1612-1639, 2013
212013
The grand old party–a party of values?
P Mair, T Rusch, K Hornik
SpringerPlus 3, 1-10, 2014
182014
Persuasibility and the self–Investigating heterogeneity among consumers
M Koller, A Floh, A Zauner, T Rusch
Australasian marketing journal 21 (2), 94-104, 2013
152013
Discussion of" 50 Years of Classification and Regression Trees"
T Rusch, A Zeileis
International Statistical Review 82, 361-367, 2014
13*2014
Tests of additivity in mixed and fixed effect two-way ANOVA models with single sub-class numbers
D Rasch, T Rusch, M Šimečková, KD Kubinger, K Moder, P Šimeček
Statistical Papers 50 (4), 905-916, 2009
132009
Extended Rasch Modeling
P Mair, R Hatzinger, MJ Maier, T Rusch
R Package2015, 2013
122013
Package eRm (extended Rasch modeling)
P Mair, R Hatzinger, M Maier, T Rusch, R Debelak
Reference manual. R package version 0.14-0. URL: http://cran. r-project. org …, 2011
112011
Cluster optimized proximity scaling
T Rusch, P Mair, K Hornik
Journal of Computational and Graphical Statistics 30 (4), 1156-1167, 2021
82021
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