In the area of quality of life research, researchers may ask respondents to rate importance as well
Importance Weighting 2
as satisfaction of various life domains (such as job and health) and use importance ratings as
weights to calculate overall, or global, life satisfaction. The practice of giving more important
domains more weight, known as importance weighting, has not been without controversy.
Several previous studies assessed importance weighting using the analytical approach of
moderated regression. This study discusses major issues related to how importance weighting
has been assessed. Specifically, this study highlights that studies on importance weighting without considering statistical power are prone to type II error, i.e., failing to reject the null hypothesis of no significant weighting effect when the null hypothesis is actually false. The sample size required for adequate statistical power to detect importance weighting functions
appeared larger than most previous studies could offer.
History
Publisher Statement
This is the author’s version of a work that was accepted for publication in Social Science Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Social Science Research, 2015. 50: 303-310. DOI: 10.1016/j.ssresearch.2014.12.009