Happiness and life satisfaction have traditionally been measured using verbal response scales, however, these verbal scales have not kept up with the present trend to use numerical response scales. A switch from a verbal scale to a numerical scale, however, causes a severe problem for trend analyses, due to the incomparability of the old and new measurements. The Reference Distribution Method is a method that has been developed recently to deal with this comparison problem. In this method use is made of a reference distribution based on responses to a numerical scale which is used to decide at which point verbally labelled response options transit from one state to another, for example from ‘happy’ to ‘very happy’. Next, for each wave of the time series in which the verbal scale is used, a population mean is estimated for the beta distribution that fits best to these transition points and the responses in this wave. These estimates are on a level that is comparable to that of the mean of the reference distribution and are appropriate for use in an extended time series based on the responses measured using a verbal and a numerical scale. In this paper we address the question of whether the transition points derived for the general population can be used for demographic categories to produce reliable, extended time series to monitor differences in trends among these categories. We conclude that this is possible and that it is not necessary to derive transition points for each demographic category separately.

Additional Metadata
Keywords Beta distribution, Comparability of rating scales, Demographic categories, Happiness, Reference distribution, Satisfaction with life
Persistent URL dx.doi.org/10.1007/s11205-015-0897-6, hdl.handle.net/1765/82042
Journal Social Indicators Research: an international and interdisciplinary journal for quality-of-life measurement
Citation
DeJonge, T, Veenhoven, R, Moonen, L, Kalmijn, W.M, van Beuningen, J, & Arends, L.R. (2016). Conversion of Verbal Response Scales: Robustness Across Demographic Categories. Social Indicators Research: an international and interdisciplinary journal for quality-of-life measurement, 126(1), 331–358. doi:10.1007/s11205-015-0897-6