| papaja: Prepare reproducible APA journal articles with R Markdown (R package version 0.1.1) F Aust, M Barth https://doi.org/10.32614/CRAN.package.papaja, 2022 | 708* | 2022 |
| tinylabels: Lightweight variable labels M Barth https://doi.org/10.32614/CRAN.package.tinylabels, 2020 | 101 | 2020 |
| Distorted estimates of implicit and explicit learning in applications of the process-dissociation procedure to the SRT task C Stahl, M Barth, H Haider Consciousness and cognition 37, 27-43, 2015 | 13 | 2015 |
| Assumptions of the process-dissociation procedure are violated in implicit sequence learning. M Barth, C Stahl, H Haider Journal of Experimental Psychology: Learning, Memory, and Cognition 45 (4), 641, 2019 | 9 | 2019 |
| Evaluating the robustness of parameter estimates in cognitive models: A meta-analytic review of multinomial processing tree models across the multiverse of estimation methods. H Singmann, DW Heck, M Barth, E Erdfelder, NR Arnold, F Aust, ... Psychological Bulletin 150 (8), 965, 2024 | 5 | 2024 |
| A Bayesian and Frequentist multiverse pipeline for MPT models—applications to recognition memory H Singmann, DW Heck, M Barth, J Groß, BG Kuhlmann | 2 | 2019 |
| Parallel acquisition of uncorrelated sequences does not provide firm evidence for a modular sequence-learning system M Barth, C Stahl, H Haider Journal of Cognition 6 (1), 2023 | 1 | 2023 |
| Toward a Questionnaire to Assess Biology Student Teachers’ Knowledge of the Nature of Scientific Inquiry (NOSI) CC Wacker, M Barth, C Stahl, K Schlüter Current Research in Biology Education: Selected Papers from the ERIDOB …, 2022 | 1 | 2022 |
| Parallel acquisition of uncorrelated sequences is hard to find M Barth, C Stahl OSF, 2024 | | 2024 |
| Relational EC MPT-Experiment 2 (RR) KC Bading, K Rothermund, M Barth OSF, 2023 | | 2023 |
| TeaP 2022-Abstracts of the 64th Conference of Experimental Psychologists S Malejka, M Barth, H Haider, C Stahl Tagung experimentell arbeitender Psychologen (TeaP), 2022, Cologne, Germany, 2022 | | 2022 |
| MPTmultiverse: Multiverse analysis of multinomial processing tree models (R package version 0.4-2) H Singmann, DW Heck, M Barth https://doi.org/10.32614/CRAN.package.MPTmultiverse, 2020 | | 2020 |
| Measuring Implicit and Explicit Sequence Learning M Barth Universität zu Köln, 2018 | | 2018 |
| Evidence for an evaluative effect of stimulus co-occurrence may be inflated by evaluative differences between assimilative and contrastive relations KC Bading, M Barth, K Rothermund | | |
| How Implicit Sequence Learning and Explicit Sequence Knowledge Are Expressed in a Serial Response Time Task M Barth, C Stahl, H Haider OSF, 0 | | |
| Sequence Learning and the Process Dissociation Procedure: How estimates of implicit and explicit knowledge are biased in the absence of associative learning M Barth, H Haider, C Stahl | | |
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