| Summary: | True and Error Theory (TET) is a modern latent variable
modeling approach for analyzing sets of preferences held by people. Individual
True and Error Theory (iTET) allows researchers to estimate the proportion of
the time an individual truly holds a particular underlying set of preferences
without assuming complete response independence in a repeated measures
experimental design. iTET is thus suitable for investigating research questions
such as whether an individual ever is truly intransitive in their preferences
(i.e., they prefer a to b, b to c, and c to a). While current iTET analysis
methods provide the means of investigating such questions they require a lot of
data to achieve satisfactory power for hypothesis tests of interest. This paper
overviews the performance and shortcomings of the current analysis methods in
efficiently using data, while providing new analysis methods that offer
substantial gains in power and efficiency.
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