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Daniel W. Heck
Daniel W. Heck
Professor of Psychological Methods, University of Marburg
Verified email at uni-marburg.de - Homepage
Title
Cited by
Cited by
Year
TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling
DW Heck, NR Arnold, D Arnold
Behavior research methods 50, 264-284, 2018
1392018
A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: The case of felt power
QF Gronau, S Van Erp, DW Heck, J Cesario, KJ Jonas, EJ Wagenmakers
Comprehensive Results in Social Psychology 2 (1), 123-138, 2017
1392017
Who lies? A large-scale reanalysis linking basic personality traits to unethical decision making
DW Heck, I Thielmann, M Moshagen, BE Hilbig
Judgment and Decision making 13 (4), 356-371, 2018
1042018
Extending multinomial processing tree models to measure the relative speed of cognitive processes
DW Heck, E Erdfelder
Psychonomic Bulletin & Review 23, 1440-1465, 2016
672016
Which is the greater good? A social dilemma paradigm disentangling environmentalism and cooperation
SA Klein, BE Hilbig, DW Heck
Journal of Environmental Psychology 53, 40-49, 2017
572017
On the relationship between Openness to Experience, political orientation, and pro-environmental behavior
SA Klein, DW Heck, G Reese, BE Hilbig
Personality and Individual Differences 138, 344-348, 2019
542019
RRreg: An R package for correlation and regression analyses of randomized response data
DW Heck, M Moshagen
Journal of Statistical Software 85 (2), 1-29, 2018
46*2018
Anonymity and incentives: An investigation of techniques to reduce socially desirable responding in the Trust Game
I Thielmann, DW Heck, BE Hilbig
Judgment and Decision Making 11 (5), 527-536, 2016
462016
metaBMA: Bayesian model averaging for random and fixed effects meta-analysis
DW Heck, QF Gronau, EJ Wagenmakers
Availabe at https://CRAN. R-project. org/package= metaBMA, 2017
45*2017
A primer on Bayesian model-averaged meta-analysis
QF Gronau, DW Heck, SW Berkhout, JM Haaf, EJ Wagenmakers
Advances in Methods and Practices in Psychological Science 4 (3 …, 2021
432021
A new model for acquiescence at the interface of psychometrics and cognitive psychology
H Plieninger, DW Heck
Multivariate behavioral research 53 (5), 633-654, 2018
432018
Linking process and measurement models of recognition-based decisions.
DW Heck, E Erdfelder
Psychological Review 124 (4), 442, 2017
392017
A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling
QF Gronau, EJ Wagenmakers, DW Heck, D Matzke
Psychometrika 84, 261-284, 2019
372019
Deciding with the eye: How the visually manipulated accessibility of information in memory influences decision behavior
C Platzer, A Bröder, DW Heck
Memory & Cognition 42, 595-608, 2014
352014
A caveat on the Savage–Dickey density ratio: The case of computing Bayes factors for regression parameters
DW Heck
British Journal of Mathematical and Statistical Psychology 72 (2), 316-333, 2019
332019
Model selection by minimum description length: Lower-bound sample sizes for the Fisher information approximation
DW Heck, M Moshagen, E Erdfelder
Journal of Mathematical Psychology 60, 29-34, 2014
312014
Revisiting REVISE:(Re) Testing unique and combined effects of REminding, VIsibility, and SElf-engagement manipulations on cheating behavior
C Schild, DW Heck, KA ¦ciga³a, I Zettler
Journal of Economic Psychology 75, 102161, 2019
302019
Interindividual differences in the sensitivity for consequences, moral norms, and preferences for inaction: Relating basic personality traits to the CNI model
M Kroneisen, DW Heck
Personality and Social Psychology Bulletin 46 (7), 1013-1026, 2020
282020
Who deals with the devil? Interdependence, personality, and corrupted collaboration
KA ¦ciga³a, C Schild, DW Heck, I Zettler
Social Psychological and Personality Science 10 (8), 1019-1027, 2019
272019
Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference
DW Heck, CP Davis-Stober
Journal of mathematical psychology 91, 70-87, 2019
262019
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