Issues in Evaluating Importance Weighting in Quality of Life Measures

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.