Open dataset for: "Social-evaluative threat: stress response stages and influences of biological sex and neuroticism"

Published: 8 November 2019| Version 11 | DOI: 10.17632/7vj8r76s6f.11
Contributors:
Eefje Poppelaars,
Johannes Klackl,
Belinda Pletzer,
Frank H. Wilhelm,
Eva Jonas

Description

Open data and R analysis scripts for the paper as published: "Poppelaars, E. S., Klackl, J., Pletzer, B., Wilhelm, F.H. & Jonas, E. (2019). Social-evaluative threat: Stress response stages and influences of biological sex and neuroticism. Psychoneuroendocrinology, 109, 104378. https://doi.org/10.1016/j.psyneuen.2019.104378. Description of the dataset: A dataset of 37 men and 30 women (tested in the luteal phase of their menstrual cycle) participated in a public speaking task to induce social-evaluative threat. Responses of multiple stress systems were measured (trait appraisal, sympathetic and parasympathetic nervous system activity, self-reported motivation and affect, and hypothalamic–pituitary–adrenal axis activity), as well as personality traits (e.g. neuroticism and extraversion). Description of files: - File 'README.txt' contains the description of the files (metadata). - File 'SETData.sav' contains the raw data. - File 'Codebook.xlsx' contains a description of all variables in the 'SET.outl.del.imp.RData' file (metadata). - File 'SET.outl.del.imp.RData' contains multiple imputed datasets (without missing values) that can be used to reproduce results from the paper. - File '01_CalculationOfData.R' is an R analysis script that imports the raw data, calculates new variables, and imputes missing data via multiple imputation using the 'predictorMatrixAdj.xlsx' file. - File '02_AnalysisOfImputedData.R' is an R analysis script that calculates descriptive statistics, creates plots, and tests hypotheses using t-tests, Bayesian statistics, and multiple lineair regressions.

Files

Steps to reproduce

To replicate results: run attached R script 2 using the imputed R dataset. To analyze other questions of interest using the same dataset: run attached R script 1 using the raw dataset.