Preprint version of this work is publicly available at **https://psyarxiv.com/gn35m** The published version of this work is openly available at https://doi.org/10.1111/bjop.12513 ---------- For any doubt or comment, feel free to email tcoll@ugr.es ---------- [As part of the data sharing process, this repository include the following files #### The task - `ANTI-VeaD_Task(E-Prime 2.0).zip` - This is the task used in our study, that is, the Attention Network Test for Interaction and Vigilance—Executive and Arousal Component (ANTI-Vea) with irrelevant distractors. To run the task in a computer it is necessary to install E-Prime 2.0 (for Windows).][0] #### Raw data - `Data_ANTI-VeaD.xlsx` - This sheet contains data of the task performance for all the participants of the study, as generated by the task. That is, raw, trial-by-trial data. Most relevant columns are highlighted in yellow and additional columns, at the right of the E-Prime-generated columns, include notes with description. - `Data_ANTI-VeaD.csv` - Similar to **Data_ANTI-VeaD.xlsx**, but in CSV format to be more easily downloaded and imported to other scripts #### R scripts for data analyses *These files, along with their input (i.e., **Data_ANTI-VeaD.xlsx**), outputs, and HTML document of analyses, are available at the Github project site (https://github.com/taocm92/ANTI-VeaD)* - `Data_Task_Treatment.R` - This script generates five tables to analyse the effect of the task manipulation across its different conditions and trials. It also generates one table with the task indexes so as to be combined with the scores obtained in the self-reports. - `Task_Split-half.R` - This script generates six tables with the reliability indexes for the type of trials in the ANTI-VeaD. These tables show each iteration conducted to obtain the permutation-based split-half reliability. The script also generates a file with a summary of the realiability and its Spearman-Brown correction for each index as well as an example to report this analysis. - `Distribution_Analysis.R` - This script conducts the procedure, analysis, and visualizations described in Supplemental Text 1 (including Figure 2 in the main text). It uses **ANTI-VeaD_(Questionnaires+Task).xlsx** as an input file. As output files, this script generates the virtual population (i.e., bootstrapped sample with 10,000 observations) and the virtual sample (i.e., a sample extracted from the quantiles of the virtual population that is equally-sized as the study sample) that has been used in our study. #### Processed database - `ANTI-VeaD_(Questionnaires+Task).xlsx` - This sheet combines the task performance, as analyzed by **Data_Task_Treatment.R**, with the questionnaires scores for each participant of the study. Notes are included in relevant columns. - `ANTI-Vea_ID_(Questionnaires+Task).csv` - Same file as **ANTI-VeaD_(Questionnaires+Task).xlsx**, but in CSV so that it can be analyzed by JASP #### Final analyses - `ANTI-VeaD_(Questionnaires_Task).jasp` - This JASP file contains the analyses included in the Result section of the manuscript, with the exception of the reliability analyses of the task. The data used correspond to **ANTI-Vea_ID_(Questionnaires+Task).csv**. Note that validity filters and type of alternative hypotheses should be correctly set.