Abstract
This article presents an advanced application of Facet Benchmarking (FB), an instrument refinement method that sets out to identify redundant and extraneous facets (Siegling, Petrides, & Martskvishvili, 2015). FB uses external benchmarks to determine whether a measure's facets each occupy unique construct variance. In Study 1, three samples completed measures of dispositional mindfulness and an objectively derived set of construct-relevant criteria. A general factor extracted from these criteria was used to benchmark the measures' facets or subscales. Structural Equation Modelling, featuring a common latent (method) factor, was incorporated as an alternative statistical procedure, indicating that statistical or methodological artefacts were unlikely to account for the obtained results. Study 2 was conducted to cross-validate the results for a benchmark derived from a different set of criteria. The results support the method's robustness and efficacy.
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