# Optimal $2^K$ Paired Comparison Designs for Third-Order Interactions

## TL;DR

This paper investigates the design of optimal paired comparison experiments in psychological research, focusing on models that include third-order interactions among attributes to improve the efficiency of data collection.

## Contribution

It introduces a methodology for constructing optimal $2^K$ paired comparison designs that account for third-order interactions, advancing experimental design theory.

## Key findings

- Developed a framework for optimal design construction with third-order interactions.
- Provided criteria for selecting efficient paired comparison designs.
- Enhanced understanding of how to incorporate complex interactions in experimental setups.

## Abstract

In psychological research often paired comparisons are used in which either full or partial profiles of the alternatives described by a common set of two-level attributes are presented. For this situation the problem of finding optimal designs is considered in the presence of third-order interactions.