pLift {cata} | R Documentation |
Penalty-Lift analysis for CATA variables, which is the difference between the average hedonic response when CATA attribute is checked vs. the average hedonic response when CATA attribute is not checked.
pLift(X, Y)
X |
either a matrix of CATA data with |
Y |
matrix of hedonic data with |
Penalty lift for the attribute if X
is a matrix; otherwise,
penalty-lift for each attribute if X
is a 3d array. If an attributes
is only checked or not check then NA
is returned.
Meyners, M., Castura, J.C., & Carr, B.T. (2013). Existing and new approaches for the analysis of CATA data. Food Quality and Preference, 30, 309-319, doi:10.1016/j.foodqual.2013.06.010
data(bread)
# penalty lift, based only on the first 12 consumers
# for the first attribute ("Fresh")
pLift(bread$cata[1:12,,1], bread$liking[1:12, ])
# for the first 3 attributes
pLift(bread$cata[1:12,,1:3], bread$liking[1:12, ])