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<h1>Subliminal influence on preferences? A test of evaluative conditioning for brief visual conditioned stimuli using auditory unconditioned stimuli</h1> <h4>Tobias Heycke, Frederik Aust, & Christoph Stahl</h4> <h4>University of Cologne</h4> <hr> <p><em>Note, this repository is intended for educational purposes. If you are professionally interested in the files shared herein, please refer to the original project repository of the publication (<a href="https://osf.io/cx5eh/" rel="nofollow">https://osf.io/cx5eh/</a>).</em></p> <hr> <h2>Description</h2> <blockquote> <p>In the field of evaluative conditioning (EC), two opposing theories—propositional single-process theory versus dual-process theory—are currently being discussed in the literature. The present set of experiments test a crucial prediction to adjudicate between these two theories: Dual-process theory postulates that evaluative conditioning can occur without awareness of the contingency between conditioned stimulus (CS) and unconditioned stimulus (US); in contrast, single-process propositional theory postulates that EC requires CS-US contingency awareness. In a set of three studies, we experimentally manipulate contingency awareness by presenting the CSs very briefly, thereby rendering it unlikely to be processed consciously. We address potential issues with previous studies on EC with subliminal or near-threshold CSs that limited their interpretation. Across two experiments, we consistently found an EC effect for CSs presented for 1000 ms and consistently failed to find an EC effect for briefly presented CSs. In a third pre-registered experiment, we again found evidence for an EC effect with CSs presented for 1000 ms, and we found some indication for an EC effect for CSs presented for 20 ms. (Heycke, Aust, & Stahl, 2017)</p> </blockquote> <p>This repository provides research products associated with the publication. We provide the experimental software and stimulus material that we are permitted to share in the <code>Material</code> directory.</p> <p>Reproduction of the reported results requires that all files in this directory are downloaded and that the folder structure is retained. To process the raw data, reproduce all analysis including figures and tables, and create the manuscript file in <code>PDF</code>-format, render the R Markdown file <code>Analyses/Heycke, Aust, & Stahl (2017) Subliminal influence on preferences.Rmd</code> using the "Knit"-Button in RStudio or the <code>render()</code>-function in the R package <code>rmarkdown</code>. The working directory is automatically set to the location of the R Markdown file; all other file paths are defined relative to this location. Similarly, by default expensive computations of Bayes factors are skipped and results are loaded from <code>Analyses/Cached computations</code>. Rerunning all analyses may take somewhere between hours and days depending on the processor of the computer and the number of cores used for parallel computing. For convenience we have also added R-script versions of the R Markdown files, which can be directly executed in R without rendering the manuscript. To run the R-script files set the working directory to the location of the script file.</p> <p>The <code>Raw data/</code> directory contains all the raw data; merged and processed data files can be found in <code>Processed data/</code>. A codebook, containing brief descriptions of the variables of each raw data file, is available at <code>Raw data/<a href="http://Codebook.md" rel="nofollow">Codebook.md</a></code>. The published version of the article can be found in <code>Research report</code>.</p> <h2>Dataset description</h2> <p>Data were collected at the lab of the Research Methods and Experimental Psychology group, Department Psychology, University of Cologne, Cologne, Germany.</p> <p>| Study | Data collection period | | ------------ | ----------------------- | | Pilot_Study1 | 2015-05-27 - 2015-06-01 | | Study1 | 2015-06-02 - 2015-06-16 | | Pilot_Study2 | 2016-03-31 | | Study2 | 2016-05-12 - 2016-05-13 | | Pilot_Study3 | 2016-05-30 | | Study3 | 2016-12-21 - 2017-05-17 |</p> <p>Descriptions of the data collection methods are provided in the study protocol and research report. Processed data are provided <code>RData</code>-format, which can be readily imported into R using <code>load()</code>. Details about the data processing steps are available in the R Markdown files in <code>Analyses/Analysis functions/</code>. We provide a codebook for the raw data in the <code>Raw data</code> directory.</p> <h2>Software requirements</h2> <h3>Experimental software</h3> <p>The experiment was programmed using PsychoPy 1.82.01 and 1.83.01. See the respective README documents in the Material subdirectories for additional information.</p> <h3>Analyses</h3> <p>Analyses were originally run on Ubuntu 14.04 using R 3.4.3 and Stan 2.16.0, and the R-packages afex 0.18.0, BayesFactor 0.9.12.2, brms 1.10.2, fitdistrplus 1.0.9, ggplot2 2.2.1, lme4 1.1.14, lsmeans 2.27.61, papaja 0.1.0.9655, rmarkdown 1.8, and rstan 2.16.2.</p> <p>To install <a href="https://github.com/crsh/papaja#installation" rel="nofollow">papaja</a> and <a href="https://github.com/paul-buerkner/brms#how-do-i-install-brms" rel="nofollow">brms</a> please review the installation instructions.</p> <h2>Publication (recommended citation)</h2> <p>Heycke, T., Aust, F., & Stahl, C. (2017). Subliminal influence on preferences? A test of evaluative conditioning for brief visual conditioned stimuli using auditory unconditioned stimuli. <em>Royal Society Open Science</em>, 4(9). <a href="https://doi.org/10.1098/rsos.160935" rel="nofollow">https://doi.org/10.1098/rsos.160935</a></p> <p>All data files, experimental scripts, and analysis scripts are also available from the original project directory of the publication (<a href="https://osf.io/cx5eh/" rel="nofollow">https://osf.io/cx5eh/</a>).</p> <h2>Acknowledgements</h2> <p>TH & CS planned and conducted Experiment 1; TH, FA & CS planned and conducted Experiments 2 and 3, analyzed the data, and wrote the article. We thank Paul Buerkner for his help with the data analysis, C. Florin, S. Gehrmann, C. Marschollek, C. Sondermann, B. Weiler, & N. Winkelmann for their help with data collection of Experiment 1, and N. Becker, H. Frings, J. Krasko, K. Mattonet, L. Moerschbacher, P. Musfeld, & L. Spitzer for the data collection of Experiments 2 and 3.</p> <h2>Funding</h2> <p>The study was funded by a grant awarded to the first author by the Graduate School of the Faculty of Human Sciences, University of Cologne, and by Deutsche Forschungsgemeinschaft Grant 1269/3-1 to the Christoph Stahl.</p> <h2>Licensing information</h2> <p>Manuscript: <a href="http://creativecommons.org/licenses/by/4.0/" rel="nofollow">CC-BY-4.0</a></p> <p>Code: <a href="http://opensource.org/licenses/MIT" rel="nofollow">MIT</a> 2017 Tobias Heycke</p> <p>Data: <a href="http://creativecommons.org/publicdomain/zero/1.0/" rel="nofollow">CC-0</a> attribution requested in reuse</p> <p>Material: - Experimental software: <a href="http://opensource.org/licenses/MIT" rel="nofollow">MIT</a> 2015-2017 Tobias Heycke - US sound files: Copyright 2017 Sascha Topolinsky - Maske.jpg: <a href="http://creativecommons.org/publicdomain/zero/1.0/" rel="nofollow">CC-0</a></p> <h2>Contact</h2> <p>Tobias Heycke Research Methods and Experimental Psychology Department Psychology University of Cologne Herbert-Lewin-Str. 2, 50931 Cologne, Germany</p> <p>E-mail: t.heycke@uni<a href="http://-koeln.de" rel="nofollow">-koeln.de</a></p> <h2>File list</h2> <p>Analyses/Analysis functions/batch_read.R Analyses/Analysis functions/BFtHDI.R Analyses/Analysis functions/printBFbrms.R Analyses/Analysis functions/printBF.R Analyses/Analysis functions/printBFt.R Analyses/Analysis functions/TrueCohensD.R Analyses/Appendix.R Analyses/Appendix.Rmd Analyses/Appendix.tex Analyses/Cached computations/aovBF_1000.RData Analyses/Cached computations/aovBFAll2.RData Analyses/Cached computations/aovBF_all3.1.RData Analyses/Cached computations/aovBF_all3.RData Analyses/Cached computations/aovBF_all3_rfirst.1.RData Analyses/Cached computations/aovBF_all3_rfirst.RData Analyses/Cached computations/aovBF_sub3expl.RData Analyses/Cached computations/aovBF_supra3expl.RData Analyses/Cached computations/aovOrderBF.RData Analyses/Cached computations/aovOrderChoiceFirstBF.RData Analyses/Cached computations/aovOrderRatingFirstBF.RData Analyses/Cached computations/Choice3.2BGLMER_samplesexplore.RData Analyses/Cached computations/Choice3.2BGLMER_samplesExploreRF.RData Analyses/Cached computations/Choice3.2BGLMER_samples.RData Analyses/Cached computations/Choice3BGLMER_samples.RData Analyses/Cached computations/choice3InclBoth.RData Analyses/Cached computations/choice3InclKnowing.RData Analyses/Cached computations/choice3IncludeSpace.RData Analyses/Cached computations/ChoiceBGLMER_samples.RData Analyses/Heycke, Aust, & Stahl (2017) Subliminal influence on preferences.pdf Analyses/Heycke, Aust, & Stahl (2017) Subliminal influence on preferences.R Analyses/Heycke, Aust, & Stahl (2017) Subliminal influence on preferences.Rmd Analyses/open-biology.csl Analyses/references.bib Analyses/r-references.bib Heycke, Aust, & Stahl (2017) Subliminal influence on preferences.pdf Material/Study1/Maske.jpg Material/Study1/read_me_Python_Study1.txt Material/Study1/<a href="http://Study1.py" rel="nofollow">Study1.py</a> Material/Study2/Maske.jpg Material/Study2/ReadMe_Python_Study2.txt Material/Study2/<a href="http://Study2.py" rel="nofollow">Study2.py</a> Material/Study2/US/n11.wav Material/Study2/US/n13.wav Material/Study2/US/n14.wav Material/Study2/US/n25.wav Material/Study2/US/n30.wav Material/Study2/US/n31.wav Material/Study2/US/n40.wav Material/Study2/US/n45.wav Material/Study2/US/n46.wav Material/Study2/US/n50.wav Material/Study2/US/neu10.wav Material/Study2/US/neu1.wav Material/Study2/US/neu2.wav Material/Study2/US/neu3.wav Material/Study2/US/neu4.wav Material/Study2/US/neu5.wav Material/Study2/US/neu6.wav Material/Study2/US/neu7.wav Material/Study2/US/neu8.wav Material/Study2/US/neu9.wav Material/Study2/US/p21.wav Material/Study2/US/p22.wav Material/Study2/US/p23.wav Material/Study2/US/p36.wav Material/Study2/US/p45.wav Material/Study2/US/p52.wav Material/Study2/US/p53.wav Material/Study2/US/p73.wav Material/Study2/US/p89.wav Material/Study2/US/p91.wav Material/Study3/Maske.jpg Material/Study3/ReadMe_Python_Study3.txt Material/Study3/<a href="http://Study3.py" rel="nofollow">Study3.py</a> Material/Study3/US/n11.wav Material/Study3/US/n13.wav Material/Study3/US/n14.wav Material/Study3/US/n25.wav Material/Study3/US/n30.wav Material/Study3/US/n31.wav Material/Study3/US/n40.wav Material/Study3/US/n45.wav Material/Study3/US/n46.wav Material/Study3/US/n50.wav Material/Study3/US/neu10.wav Material/Study3/US/neu1.wav Material/Study3/US/neu2.wav Material/Study3/US/neu3.wav Material/Study3/US/neu4.wav Material/Study3/US/neu5.wav Material/Study3/US/neu6.wav Material/Study3/US/neu7.wav Material/Study3/US/neu8.wav Material/Study3/US/neu9.wav Material/Study3/US/p21.wav Material/Study3/US/p22.wav Material/Study3/US/p23.wav Material/Study3/US/p36.wav Material/Study3/US/p45.wav Material/Study3/US/p52.wav Material/Study3/US/p53.wav Material/Study3/US/p73.wav Material/Study3/US/p89.wav Material/Study3/US/p91.wav Processed data/choiceData3InclBoth.RData Processed data/choiceData3InclKnowing.RData Processed data/choiceData3IncludeSpace.RData Processed data/choiceData3.RData Processed data/ChoiceData.RData Processed data/DemoData2.RData Processed data/DemoData3.RData Processed data/DemoData.RData Processed data/KnowingData2.RData Processed data/KnowingData3.RData Processed data/ratingData2.RData Processed data/ratingData3includeSpaceguys.RData Processed data/ratingData3.RData Processed data/ratingData3wideSpaceExcl.RData Processed data/ratingDataAggr3SpaceandKnowingOut.RData Processed data/ratingData.RData Processed data/ratingPicsCroCo2Pilot.RData Processed data/TrialData3.RData Processed data/visCroco3.RData Processed data/VisibilityData2.RData Processed data/VisibilityDataCroco3Pilot.RData Processed data/VisibilityData.RData Raw data/<a href="http://Codebook.md" rel="nofollow">Codebook.md</a> Raw 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data/Study3/Order_Croco3_87.txt Raw data/Study3/Order_Croco3_88.txt Raw data/Study3/Order_Croco3_89.txt Raw data/Study3/Order_Croco3_8.txt Raw data/Study3/Order_Croco3_90.txt Raw data/Study3/Order_Croco3_91.txt Raw data/Study3/Order_Croco3_92.txt Raw data/Study3/Order_Croco3_93.txt Raw data/Study3/Order_Croco3_94.txt Raw data/Study3/Order_Croco3_95.txt Raw data/Study3/Order_Croco3_96.txt Raw data/Study3/Order_Croco3_97.txt Raw data/Study3/Order_Croco3_98.txt Raw data/Study3/Order_Croco3_99.txt Raw data/Study3/Order_Croco3_9.txt <a href="http://README.md" rel="nofollow">README.md</a> Study protocol (Stage-1 registered report).pdf</p>
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