analyse_holos: Analyse Holos data
In SensoMineR: Sensory Data Analysis

Description Usage Arguments Value References See Also Examples

Provide numeric tools and graphical tools to analyse Holos data.

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

`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.

`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).

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.

format_holos

## Not run: 
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)

## End(Not run)