Formalizing Agreement Analysis For Elicitation Studies: New Measures, Significance Test, And Toolkit

We address in this work the process of agreement rate analysis for characterizing the level of consensus between participants' proposals elicited during guessability studies. Two new measures, i.e., disagreement rate for referents and coagreement rate between referents, are proposed to accompany the widely-used agreement rate formula of Wobbrock et al. [37] when reporting participants' consensus for symbolic input. A statistical significance test for comparing the agreement rates of k >= 2 referents is presented in analogy with Cochran's success/failure Q test [5], for which we express the test statistic in terms of agreement and coagreement rates. We deliver a toolkit to assist practitioners to compute agreement, disagreement, and coagreement rates, and run statistical tests for agreement rates at p = .05, .01, and .001 levels of significance. We validate our theoretical development of agreement rate analysis in relation with several previously published elicitation studies. For example, when we present the probability distribution function of the agreement rate measure, we also use it (1) to explain the magnitude of agreement rates previously reported in the literature, and (2) to propose qualitative interpretations for agreement rates, in analogy with Cohen's guidelines for effect sizes [6]. We also re-examine previously published elicitation data from the perspective of the agreement rate test statistic, and highlight new findings on the effect of referents over agreement rates, unattainable prior to this work. We hope that our contributions will advance the current knowledge in agreement rate analysis, providing researchers and practitioners with new techniques and tools to help them understand user-elicited data at deeper levels of detail and sophistication.