sensory.mr.dimensionality.test: Multiple-response dimensionality test for sensory data

In MahieuB/MultiResponseR: Analysis of Data from Multiple-Response Questionnaires

Multiple-response dimensionality test for sensory data

Description

Performs a multiple-response dimensionality test as defined in Mahieu, Schlich, Visalli, and Cardot (2021) using random permutations to estimate the null distribution. The difference with mr.dimensionality.test is that random permutations are performed within subjects rather than along all evaluations

Usage

sensory.mr.dimensionality.test(data, nperm = 2000, alpha = 0.05)

Arguments

data	A data.frame of evaluations in rows whose first two columns are factors (subject and product) and subsequent columns are binary numeric or integer, each column being a descriptor
nperm	Number of permuted datasets to estimate the distribution of the statistic under the null hypothesis. See details
alpha	The alpha risk of the test

Details

• nperm: The distribution of the statistic under the null hypothesis of no associations between products and descriptors is estimated using nperm datasets generated thanks to random permutations of the response vectors along products within subjects.

Value

A list with the following elements:

dim.sig

The number of significant dimensions

statistics

Observed multiple-response chi-square statistic of each dimension

p.values

P-value of the test of each dimension adjusted for closed testing procedure

References

Loughin, T. M., & Scherer, P. N. (1998). Testing for Association in Contingency Tables with Multiple Column Responses. Biometrics, 54(2), 630-637.

Mahieu, B., Schlich, P., Visalli, M., & Cardot, H. (2021). A multiple-response chi-square framework for the analysis of Free-Comment and Check-All-That-Apply data. Food Quality and Preference, 93.

Examples

data(milkchoc)

sensory.mr.dimensionality.test(milkchoc)

MahieuB/MultiResponseR documentation built on June 22, 2024, 8:08 a.m.