For most empirical research investigating the topic of importance weighting in quality of life (QoL) measures, the prevailing approach has been to use (1) a limited choice of global QoL measures as criterion variables (often a single one) to determine the performance of importance weighting, (2) a limited option of weighting methods to develop importance weighting, and (3) a limited number of domains to construct the (formative-indicator) measures. Although limitations resulted from a limited choice of global QoL measures as criterion variables to determine the performance of importance weighting and a limited option of weighting methods to develop importance weighting have been recognized previously, little attention has been paid to the impact of non-comprehensive domains in QoL measures constructed based on the formative-indicator approach. Using empirical data, this article revealed the potential impacts of non-comprehensive domains on the evaluation of importance weighting in QoL measures. Results presented in this article showed that both of the two most popular methods of evaluating the performance of importance weighting in QoL measures, correlation and moderated regression analysis, could produce misleading results in the situation when QoL measures constructed using the formative-indicator approach did not include comprehensive domains. Issues discussed in this article are of great importance to research in the field of QoL, especially on the topic of importance weighting in QoL measures.