An Empirical Method for Causal Inference of Constructs for QoE in Haptic–Audiovisual Communications

Abstract

This article proposes an empirical method for inferring causal directions in multidimensional Quality of Experience (QoE) in multimedia communications, noting that causation in QoE is perceptual. As an example for modeling framework, we pick up a Bayesian structural equation model (SEM) previously built for haptic audiovisual interactive communications. The SEM includes three constructs (Audiovisual quality, Haptic quality, and User experience quality), which are latent variables each representing a group of observed variables with similar characteristics. In the SEM, the causal directions of the constructs were assumed by resorting to the domain knowledge. This article aims at proposing a methodology for inferring causal directions of constructs in general by verifying the assumption of causal directions in the SEM through their observed data alone. For that purpose, we compare six SEMs each with different causal directions of constructs, one of which is the one from the domain knowledge. The proposed method is based on QoE prediction by a Bayesian approach with Markov chain Monte Carlo (MCMC) simulation. Setting observed scores to the indicators of exogenous variables in each SEM, we predict values of all the indicators; we then assess the mean square error (MSE) between predicted QoE and mean opinion score (MOS) from observed scores and estimate the probability distribution of the MSE in each SEM. We can compare any two SEMs to find which is more plausible by examining the probability that the MSE for one SEM is smaller than or equal to that for the other. These probabilities are estimated with MCMC simulation. The method indicates that the causal directions thus inferred for the haptic audiovisual interactive communications adequately support the original ones drawn from the domain knowledge. In addition, we demonstrate that QoE can behave like the “impact-perceive-adapt” model of the effects of delayed haptic and visual feedback on performance in a collaborative environment, which Jay, Glencross, and Hubbold proposed in 2007, and that it accompanies reversal of plausible causal directions like a flip–flop.