Measurement invariance and adapted preferences: evidence for the ICECAP-A and WeRFree instruments

Self-report instruments are used to evaluate the effect of interventions. However, individuals adapt to adversity. This could result in individuals reporting higher levels of well-being than one would expect. It is possible to test for the influence of adapted preferences on instrument responses using measurement invariance testing. This study conducts such a test with the Wellbeing Related option-Freedom (WeRFree) and ICECAP-A instruments.

A multi-group confirmatory factor analysis was conducted to iteratively test four increasingly stringent types of measurement invariance: (1) configural invariance, (2) metric invariance, (3) scalar invariance, and (4) residual invariance. Data from the Multi Instrument Comparison study were divided into subsamples that reflect groups of participants that differ by age, gender, education, or health condition. Measurement invariance was assessed with (changes in) the Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Root Mean Square Residual (SRMR) fit indices.

For the WeRFree instrument, full measurement invariance could be established in the gender and education subsamples. Scalar invariance, but not residual invariance, was established in the health condition and age group subsamples. For the ICECAP-A, full measurement invariance could be established in the gender, education, and age group subsamples. Scalar invariance could be established in the health group subsample.

This study tests the measurement invariance properties of the WeRFree and ICECAP-A instruments. The results indicate that these instruments were scalar invariant in all subsamples, which means that group means can be compared across different subpopulations. We suggest that measurement invariance of capability instruments should routinely be tested with a reference group that does not experience a disadvantage to study whether responses could be affected by adapted preferences.