### **GENERAL INFORMATION** #### **Preliminary title of study** "A Replication of Tomlinson et al. (2013) - Possibly all of that and then some" #### **Author Information** 1. **Name**: Timo B. Roettger **Institution**: University of Osnabrück, Institute of Cognitive Science **Email**: timo.b.roettger@gmail.com 2. **Name**: Mathias Stoeber **Institution**: University of Osnabrück, Institute of Cognitive Science 3. **Name**: Michael Franke **Institution**: University of Osnabrück, Institute of Cognitive Science #### **Date of data collection**: Pilot Data: October 2019 - January 2020 Data: to be collected #### **Geographic location of data collection** Osnabrück, Germany ---------- ### **SHARING/ACCESS INFORMATION** #### **Licenses/restrictions placed on the data**: CC0-BY 4.0 ---------- ### **DATA & FILE OVERVIEW** #### **Data Analysis Component** - **`CodeBook for derivedDF.rtf`**: Contains information about all variables relevant for plotting and statistical analysis. - **`derived_data`**: - `derivedDF.csv` (data files generated during the preprocessing stage) - `posteriors_cluster_probs.csv`, `posteriors_cluster_logodds.csv`, `posteriors_output_cond.csv` (summaries of posterior extractions) - `fakeData.csv` (the fake data simulated for the power analysis, relevant for plotting and modelling) - **`models`**: Contains model output generated by `02_modeling.R` - **`plots`**: Contains publication ready plots generated by `01_plotting.R` - **`raw_data`**: Contains raw data files generated by Open Sesame in `.csv`, including the `Pilot 1-3/pilot_03` which served as the input for all statistical scripts. - **`scripts`** Contains R scripts to process, analyze and plot data: - `00_preprocessing.R` prepares the raw mousetracking data for further processing and stores the data tables in `derived_data`. - `01_plotting.R` generates figures for manuscript and stores them in `plots`. - `02_modelling.R` runs Bayesian hierarchical models and extracts posteriors. It stores posteriors into `derived_data` and the model into `models`. It further plots the results against the data and stores them in `plots`. - `03_simulateData.R` simulates fake data based on the pilot data and runs a power analysis. It stores the outcome in `derived_data` and generates a power curve plot, stored in `plots`. #### **Materials Component** - **instructions and forms**: Contains two PDF files: - the instructions issued to all participants - the consent form all participants were asked to sign before their participation - **OSexp files**: Contains the four OpenSesame experiment files. - **materials**: Contains the stimuli for training and test phase: `training.csv`,`test.csv`. ---------- ### **METHODOLOGICAL INFORMATION** #### **Instrument- or software-specific information needed to interpret the data**: @Mathias her I usually post my specs, R version and package version. Is there a meaningful way to do that when collaborating? R version 3.5.0 (2018-04-23) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: macOS 10.15 the attached packages: rstan_2.19.2 StanHeaders_2.19.0 mousetrap_3.1.0 readbulk_1.1.0 ggpubr_0.1.7 magrittr_1.5 rstudioapi_0.9.0 gridExtra_2.3 brms_2.3.5 Rcpp_1.0.2 stringr_1.4.0 dplyr_0.8.3 readr_1.3.1 tidyr_1.0.0 tibble_2.1.3 ggplot2_3.2.1 tidyverse_1.2.1 #### **People involved with sample collection, processing, analysis and/or submission**: Timo B. Roettger Mathias Stoeber Michael Franke Monika Tröber (participant acquisition & data collection)