Ratings of associations between car models and car attributes

Description

The data describe the ratings of 78 respondents about the association between each of 14 car models and each of 27 car attributes.

Usage

data(car)

Format

The data consist of a list of 4 objects:

1. datalongformat: A data frame that consists of 6 components: Each row of the data frame describes the outcome of a binary rater judgement about the association between a certain car and a certain attribute. The components IDobject and objectlabel contain an ID and label for the car models, the components IDattribute and attributelabel contain an ID and label for the attributes, the component IDrater contains a rater ID, and the component rating contains the binary ratings (1 if the car model has the attribute according to the rater, and 0 otherwise).

2. data3w: A 78 X 14 X 27 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.

3. freq1: A 14 X 27 matrix of frequencies. The frequency in cell (j,k) indicates how many of 78 respondents indicate an association between car model j and attribute k.

4. freqtot: A 14 X 27 matrix of frequencies. The frequency in cell (j,k) indicates the total number of respondents who judged the car-attribute pair (j,k).

Source

Van Gysel, E. (2011). Perceptuele analyse van automodellen met probabilistische feature modellen. [translation from Dutch: Perceptual analysis of car models with probabilistic feature models] Master thesis. Hogeschool-Universiteit Brussel.

References

Meulders, M. (2013). An R Package for Probabilistic Latent Feature Analysis of Two-Way Two-Mode Frequencies. Journal of Statistical Software, 54(14), 1-29. URL http://www.jstatsoft.org/v54/i14/.

Results