plift {cata} | R Documentation |
Penalty-Lift Analysis
Description
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.
Usage
plift(X, Y, digits = getOption("digits"), verbose = FALSE)
Arguments
X |
either a matrix of CATA data with |
Y |
matrix of hedonic data with |
digits |
for rounding |
verbose |
set to |
Value
Penalty lift per attribute, with counts and averages if verbose
is TRUE
.
Author(s)
J.C. Castura
References
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
Examples
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, ], digits = 3)
# for the first 3 attributes with counts and averages
plift(bread$cata[1:12,,1:3], bread$liking[1:12, ], digits = 3, verbose = TRUE)