Data characteristics report"
In esmtools: Preprocessing Experience Sampling Method (ESM) Data

# Setup settings
knitr::opts_chunk$set(message=FALSE, warning=FALSE)

This template follows the preprocessing framework described in Revol et al. (2023) and is stored in the R package esmtools. Additional instructions on creating reports and also on preprocessing ESM data can be found on the ESM Preprocessing Gallery website.

Import

Import package

library(ggplot2)

Import dataset

if(exists(params) && !is.na(params$file_path)){
    file_path = params$file_path_preproc
} else {
    file_path = "path/data_file.csv"
}
data = read.csv(file_path)

Session and Dataset info:

sessionInfo()

# The function dataInfo() from the esmtools package can provide further information of the dataset

Meta-info of the Preprocessed dataset:

esmtools::dataInfo(file_path=file_path, read_fun = read.csv,
                   idvar="id", timevar="sent")

Codebook table

In the table provided below, you will discover detailed information regarding each variable.

Study and data characteristics

Following, you will find a selection of plot and descriptive analysis that give insight into important aspects of how well the data follow the pre-defined sampling scheme and the study design, as well as whether participants engaged in problematic response behaviors (e.g., careless responding).

Overview

This section provides information about the global characteristics of the dataset (e.g., patterns of the missing values).

Design and sampling scheme

Following, there are descriptive analyses and plots that give insight into the actual sample scheme and study design of the data.

Participants' response behaviors

In this section, we provide insight into the extent to which the participants adhered to the sampling scheme and study design.

Variables and processes descriptions

This section gives insight into the variables themselves (e.g., distribution, correlation plots). In particular, a selection of relevant plots are displayed that help to investigate the within- and between-person differences (e.g., in time series, variable distributions), and patterns (e.g., variation of responses in function of a time variable). Additionally, a sub-section contains a participant book providing specific data information about each participant.

Participant book

In the table below, you will find comprehensive information about each participant, including the start and end times of their participation, their response behaviors (e.g., compliance), as well as their time series and histogram data for the two variables of interest.