analyse_holos: Analyse Holos data

Description

Provide numeric tools and graphical tools to analyse Holos data.

Usage

analyse_holos(data, method, axes = c(1, 2), graph = TRUE, export.res = FALSE)

Value

IDsubjects: A dataframe containing the concordance between the names of the subjects as given in the Holos experiment and their ID.
summary.task: The summary of the task realized by the subjects with pieces of information such as the number of steps performed by each subject, the duration of the task, etc.
res.FA: The results of the factorial analysis as returned by the MFA function of the FactoMineR package for Napping data, by the MCA function for Sorting data, and by the HMFA function for Sorted Napping data.
datasets: All the individuals data sets (digit-tracking data of each subject) and panel data sets (merged final configurations and verbalization).

Arguments

data: A list of object, as returned by the format_holos function.
method: A string corresponding to the holistic task realized by the subjects during the experiment: "N" for Napping task, "S" for Sorting task, or "SN" for Sorted Napping task.
axes: A length 2 vector specifying the components of the factorial analysis to plot. By default, the first two components are plotted.
graph: A boolean specifying if the graphical outputs of the factorial analysis should be plotted or not. By default, graph = TRUE.
export.res: A boolean specifying if all the graphical outputs should be exported in the working directory or not. By default, export.res = FALSE. NB: If method = "N", setting this argument to TRUE is the only way to access the individual cognitive processes.

References

Le, M.T., Brard, M. & Le, S. (2016). Holos: A collaborative environment for similarity-based holistic approaches. Behavior Research Methods.
Le, M.T., Husson, F. & Le, S. (2014). Digit-tracking: Interpreting the evolution over time of sensory dimensions of an individual product space issued from Napping and sorted Napping. Food Quality and Preference.

Examples

Run this code

if (FALSE) {
data(videos)

# Example with Napping data
res.N <- analyse_holos(videos, method = "N", export.res = TRUE)
res.N$summary.task$nbstep.time # number of steps and duration of the task for each subject
res.N$summary.task$freq[[1]] # number of times the first subject moved each stimulus during the task
res.N$res.FA # MFA results that can be customized with the plot.MFA function of FactoMineR
res.N$datasets$digitdata[[1]] # digit-tracking data of the first subject
res.N$datasets$finaldata # Napping data (panel level)

# Example with Sorting data
res.S <- analyse_holos(videos, method = "S")
res.S$res.FA # MCA results that can be customized with the plot.MCA function of FactoMineR
res.S$datasets # Sorting data (panel level)
sorting.data <- apply(res.S$datasets, 2, as.factor) ?
res.fast <- fast(sorting.data)
ConsensualWords(res.fast)
}