Open dataset for: "Reflecting on existential threats elicits self-reported negative affect but no physiological arousal"
Description
Open data and R analysis scripts for the paper as submitted for publication: "Poppelaars, E. S., Klackl, J., Scheepers, DT, Mühlberger, C., & Jonas, E. (2019). Reflecting on existential threats elicits self-reported negative affect but no physiological arousal." A dataset of 171 undergraduate students were randomly allocated to one of four existential threat conditions: mortality salience, freedom restriction, uncontrollability, and uncertainty; or to the non-existential threat condition: social-evaluative threat; or to a control condition (TV salience). Three facets of arousal were measured: positive and negative affect before and after reflection, subjective arousal during baseline and reflection, and physiological activation during baseline and reflection (electrodermal, cardiovascular, and respiratory), as well as personality traits (e.g. trait avoidance and approach, self-esteem). Description of files: - File 'README.txt' contains the description of the files (metadata). - File '20191024_IJMData_brief.sav' contains the raw data. - Files 'EXI.outl.del.RData' contains the complete dataset with missing values, with extra variables calculated, and with outliers deleted. - File 'Codebook_EXI.outl.del.csv' contains a description of all variables in the 'EXI.outl.del.RData' file (metadata). - Files 'EXI.outl.del.imp.RData' and 'EXI.outl.del.imp.extra.RData' contain 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. Also uses the custom functions: 'BF.evidence.R', 'cohen.d.magnitude.R' and 'p.value.sig.R'.