The data consist of the binary judgements of 147 respondents about the association between each of 12 car models and each of 23 car attributes.
data(car2)The data consist of a list of 5 objects:
data3w: A 147 X 12 X 23 array of binary judgements. The observation in cell (i,j,k) equals 1 if respondent i indicates that car j has attribute k, and 0 otherwise.
freq1: A 12 X 23 matrix of frequencies. The frequency in cell (j,k) indicates how many of 147 respondents indicate an association between car model j and attribute k.
freqtot: A 12 X 23 matrix of frequencies. The frequency in cell (j,k) indicates the total number of respondents who judged the car-attribute pair (j,k).
Meulders, M. and De Bruecker, P. (2018). Latent class probabilistic latent feature analysis of three-way three-mode binary data. Journal of Statistical Software, 87(1), 1-45.