InertiaPermutedTables: 'InertiaPermutedTables' A function to Compute the inertia of...

In HerveAbdi/PTCA4CATA: Partial Triadic Analysis (PTCA) for Check All That Apply (CATA) Data

InertiaPermutedTables A function to Compute the inertia of a set of random permutations of the "Check-Mark" (e.g. CATA) type of data.

Description

InertiaPermutedTables creates a cube of data from the results of a "Check-Mark" data set collected in DataChecks. These data correspond to participants matching (or not) one Descriptor to each stimulus of a set of stimuli. The Stimuli are the columns of DataChecks The Participants are the rows of DataChecks The Descriptors are the numbers in DataChecks (i.e., 5 for Datacheks[2,3] means that Participant 2, chose Descriptor 5 for Stimulus 3)

Usage

InertiaPermutedTables(DataChecks, nPerm = 1000)

Arguments

DataChecks	An I*J matrix storing integers. I are Participants, J are Stimuli. The entries in Datacheks are integers that match the descriptors (i.e., 5 for Datacheks[2,3] means that Participant 2
nPerm	number of random permutations (default = 1000). Note that the number of Descriptors is "guessed" by the program as the largest number is the dataset.

Value

returns a 1*nPerm vector with the nPerm values of the inertia computed with the nPerm random Permutations.

Author(s)

Hervé Abdi

Examples

## Not run: 
RandomnInertia <- InertiaPermutedTables(ACubeOfDataChecks)

## End(Not run)

HerveAbdi/PTCA4CATA documentation built on July 17, 2022, 5:41 a.m.