Technical Report: Confidence Intervals and Consumer Relevance


Difference testing methods such as the
Triangle, Duo-Trio, Tetrad, and 2-Alternative Forced Choice
(2–AFC) generate choice counts or numbers of correct
responses that are often analyzed statistically as binomial
variables. This analysis approach provides the basis for
hypothesis tests for difference testing methods and for
commonly available tables for that purpose. Since any
difference can be shown to be significant with a sufficiently
large sample size, there has recently been increasing
interest in using difference tests to measure the size of
sensory differences using Thurstonian theory. Concurrent
with this shift in perspective away from hypothesis testing
and towards effect size estimation has been a desire to
quantify the precision of these measurements. Along with
these developments, the importance of determining the size
of consumer-relevant differences has also become apparent.
For all these reasons, in this report we will consider the use
of confidence intervals to help with the interpretation of
sensory differences obtained through Thurstonian scaling
and to make use of the precision of these estimates.

A value in converting choice outcomes to Thurstonian
scaled estimates of delta, a standard measure of sensory difference,

is that it allows a comparison of methodologies on
a common basis and has provided empirically supported
predictions about the relative power of different methods.
This insight was recently used to support a switch from
the Triangle test to the Tetrad test and earlier provided
a very satisfying explanation for the large difference in
power between the 3-AFC and the Triangle test. The
experimental estimate of delta, called d', can be obtained easily
from many methods and it is of interest to provide a way
of calculating confidence intervals for delta and comparing the
results to consumer-relevant specifications.

This technical report appears as:

Ennis, D. M., Rousseau, B., and Ennis, J. M. (2014). Confidence Intervals and Consumer Relevance. IFPress, 17(2) 3-4.

Download this technical report here:

Confidence Intervals and Consumer Relevance

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