This SleepRestrictionReinforcementLearning_README.txt file was generated on 2020-12-01 by ANDREAS GERHARDSSON GENERAL INFORMATION =============================================================================== 1. Title of Dataset Sleep Restriction and Reinforcement Learning 2020 - Data Analysis 2. Author Information A. Principal Investigator Contact Information Name: Johanna Schwarz Institution: Stockholm University Address: Department of Psychology, 106 91 Stockholm, Sweden Email: johanna.schwarz@su.se B. Associate or Co-investigator Contact Information Name: Andreas Gerhardsson Institution: Stockholm University Address: Department of Psychology, 106 91 Stockholm, Sweden Email: andreas.gerhardsson@su.se C. Alternate Contact Information Name: John Axelsson Institution: Stockholm University Address: Department of Psychology, 106 91 Stockholm, Sweden Email: john.axelsson@su.se 3. Date of data collection (single date, range, approximate date): 2016-07 - 2016-10 4. Geographic location of data collection: Stockholm, Sweden 5. Information about funding sources that supported the collection of the data: - SHARING/ACCESS INFORMATION =============================================================================== 1. Licenses/restrictions placed on the data: CC by 4.0 2. Links to publications that cite or use the data: https://doi.org/10.1111/jsr.13236 3. Links to other publicly accessible locations of the data: 10.17045/sthlmuni.11955939 4. Links/relationships to ancillary data sets: - 5. Was data derived from another source? 6. Recommended citation for this dataset: Gerhardsson A, Porada K D, Lundström N J, Axelsson J & Schwarz J (2020) Data from: Does insufficient sleep affect how you learn from reward or punishment? – Reinforcement learning after two nights of sleep restriction. 10.17045/sthlmuni.11955939 DATA & FILE OVERVIEW 1. File List: Sleep Restriction and Reinforcement Learning - Data Analysis | - data/ | - pst_full_data.txt | - scripts/ | - pst_cm_1_fit.R | - pst_cm_2_preanalysis.R | - pst_cm_3_analysis.R | - pst_kss.R | - pst_lp_rt.R | - pst_lp_winstay_loseshift.R | - pst_plot_fnc.R | - pst_supplementary.R | - pst_test_phase_rt.R | - pst_test_phase.R | - RL_regressors_1a.stan | - RL_regressors.stan 2. Relationship between files, if important: Models, plots and tables are produced by the scripts 3. Additional related data collected that was not included in the current data package: Mean aggregation of two nights of actigraph data is provided in this data set 4. Are there multiple versions of the dataset? yes/no No METHODOLOGICAL INFORMATION =============================================================================== 1. Description of methods used for collection/generation of data: 2. Methods for processing the data: win-stay and lose-shift was calculated for each participant by sleep condition and symbol pair. win-stay = 1 if stay = 1 and feedback = positive, else win-stay = 0. lose-shift = 1 if stay = 0 and feedback = negative, else lose-shift = 0. 3. Instrument- or software-specific information needed to interpret the data: Software and packages required to run analyses, install may also include other package dependencies R (https://www.r-project.org/) Packages: bayesplot - Gabry J, Mahr T (2019). “bayesplot: Plotting for Bayesian Models.” Rpackage version 1.7.0 package version 1.7.0 bayestestR - Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541. doi:10.21105/joss.01541 brms - Paul-Christian Bürkner (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software, 80(1), 1-28. doi:10.18637/jss.v080.i01 ggplot2 - H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. ggpubr - Alboukadel Kassambara (2019). ggpubr: 'ggplot2' Based Publication Ready Plots. R package version 0.2.4. https://CRAN.R-project.org/package=ggpubr gridExtra - Baptiste Auguie (2017). gridExtra: Miscellaneous Functions for "Grid" Graphics. R Graphics. R package version 2.3. https://CRAN.R-project.org/package=gridExtra plyr - Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. URL http://www.jstatsoft.org/v40/i01/. rstanarm - Goodrich B, Gabry J, Ali I & Brilleman S. (2018). rstanarm: Bayesian applied regression modeling via Stan. R package version 2.17.4. http://mc-stan.org/ see - Daniel Lüdecke, Dominique Makowski, Philip Waggoner and Mattan S. Ben-Shachar (2019). see: Visualisation Toolbox for 'easystats' and Extra Geoms, Themes and Color Palettes for 'ggplot2'. R package version 0.3.0. https://CRAN.R-project.org/package=see shinystan - Jonah Gabry (2018). shinystan: Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models. R package version 2.5.0. https://CRAN.R-project.org/package=shinystan wesanderson - Karthik Ram and Hadley Wickham (2018). wesanderson: A Wes Anderson Palette Generator. R package version 0.3.6. https://CRAN.R-project.org/package=wesanderson Software used to perform Probalisitic Selection Task Inquisit 4 (www.millisecond.com) 4. Standards and calibration information, if appropriate: - 5. Environmental/experimental conditions: Two nights of sleep restriction vs normal night sleep 6. Describe any quality-assurance procedures performed on the data: see published article 7. People involved with sample collection, processing, analysis and/or submission: see published article DATA-SPECIFIC INFORMATION FOR: pst_full_data.txt 1. Number of variables: 42 2. Number of cases/rows: 13140 3. Variable List: Variable // Description Code // subject + sleep condition + order subject // Subject ID sleep // sleep condition character sr // sleep restriction (1 = yes, =, no) BaselineFirst // order of sleep condition (1 = normal sleep first, 0 = Sleep restriction first) female // gender (1 = female, 0 = male) age // Age in years night // not relevant days_between_tests // days between tests testtime // time of test HH:MM:SS default origin blockcode // block code of PST (learning phase or test phase) blocknum // block number of PST (first block = 4) trialcode // trial code of PST (symbol + order + phase) trialnum // trial number, originally including all events (responses etc.) stimulusitem1 // experiment path to symbol 1, not relevant for analysis, see Figur 1 in manuscript. stimulusitem2 // experiment path to symbol 2, not relevant for analysis, see Figur 1 in manuscript. values.winletter // which symbol to win response_key // response key number on keyboard values.selectedletter // symbol chosen correct // correct during learning phase = positive feedback, during test phase = best option response_time_ms // response time in milliseconds expressions.percA_ab // cumulative proportion correct for symbol pair AB expressions.percC_CD // cumulative proportion correct for symbol pair CD expressions.percE_EF // cumulative proportion correct for symbol pair EF Bed time // Bedtime according to actigraph Get up time // get up time according to actigraph Time in bed // Time in bed according to actigraph Sleep start // Sleep start according to actigraph Sleep end // Sleep end according to actigraph Assumed sleep // Assumed sleep according to actigraph Actual sleep time // Actual sleep according to actigraph (H:M:S) Actual sleep (%) // Actual sleep percent according to actigraph Actual wake time // Actual wake according to actigraph (H:M:S) Actual wake (%) // Actual wake percent according to actigraph Sleep efficiency // Sleep efficiency percent according to actigraph Sleep latency // Sleep latency according to actigraph (H:M:S) get_up_easy // sleep diary easy to get up (5 = very easy, 1 = very difficult) well_rested // well rested after sleep (5 = fully, 1 = not at all) KSS // Karolinska sleepiness scale SUSS // Subjective stress scale kss_rt_ms // Karolinska sleepiness scale, response time in milliseconds stress_rt_ms // Subjective stress scale, response time in milliseconds 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: -