This respository includes the supplementary materials of the article:

Menghini, L., Fuochi, G., Sarlo, M. Inter- and intraindividual relationships between vagally-mediated heart rate variability and self-regulatory processes: An ecological momentary assessment

The data pre-processing and data analysis are still ongoing.

The repository includes the following materials:

1. ESMeasures: Experience sampling measures used in the study (screenshots in Italian and English translations), and related protocols and Probe Definition JSON files used with the Sensus Mobile app (Xiong et al., 2016).

2. preProcessing: R code and generated report with full outputs of the pre-processing procedures applied to the raw data (available upon request to the corresponding author). The data pre-processing report is depicted at this page.

3. data: datasets (in both .RData and .csv format) generated with the data pre-processing script:

   • long: long-form dataset with time-varying variables and repeatedly recorded time-invariant variables
   • wide: wide-form dataset with demographic variables and individual averages of time-varying variables

4. psychomeDesc: R code and generated report with full outputs of the psychometric and descriptive analyses applied to the pre-processed data, including the inspection of univariate and bivariate distributions. The psychometrics and descriptives report is depicted at this page and can be reproduced by running the .Rmd script on the two datasets in 3data.

5. regModels: R code and generated report with full outputs of the generalized linear mixed-effects regression (GLMER) analysis of the pre-processed data. The data analysis report is depicted at this page and can be reproduced by running the .Rmd script on the two datasets generated with the 4psychomeDesc script.

The scripts included in this repository are based on the following external resources:

Shiny app used to pre-process the blood volume (BVP) pulse data and derive the HRV measures used in the analyses.

The data pre-processing and data analysis scripts are based on the following R packages: