homogeneity: Calculate within-cluster homogeneity

In cata: Analysis of Check-All-that-Apply (CATA) Data

Calculate within-cluster homogeneity

Description

Within a group of N consumers, the Homogeneity index lies between 1/N (no homogeneity) to 1 (perfect homogeneity).

Usage

homogeneity(X, oneI = FALSE, oneM = FALSE)

Arguments

X	three-way array; the I, J, M array has I assessors, J products, M attributes where CATA data have values 0 (not checked) and 1 (checked)
oneI	indicates whether calculation is for one assessor (default: FALSE)
oneM	indicates whether calculation is for one attribute (default: FALSE)

Value

homogeneity index

References

Llobell, F., Cariou, V., Vigneau, E., Labenne, A., & Qannari, E. M. (2019). A new approach for the analysis of data and the clustering of subjects in a CATA experiment. Food Quality and Preference, 72, 31-39, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.foodqual.2018.09.006")}

Examples

data(bread)

# homogeneity index for the first 7 consumers on the first 6 attributes
homogeneity(bread$cata[1:7,,1:6])

cata documentation built on Oct. 8, 2024, 9:07 a.m.