Once the scores for individual questions have been standardised, the next task is to aggregate them based on the framework that we presented in Figure 2.1 (and the question list available in the report). Using this hierarchical structure, it is possible to aggregate up to different levels. So, for example, one might bring together just the three positive emotional well-being questions. Or, one might bring these together with the negative emotional well-being questions to produce an overall emotional well-being score. Or, one might, in turn, bring these together with all the other personal well-being components, to produce a personal well-being index. Or, finally, one might decide to combine this with a social well-being index to produce an overall well-being index. How far one goes up the hierarchy depends on what your research questions are. For government, this depends on which of the questions mentioned earlier they are trying to answer.
At each level, the higher level indicator score is calculated by simply taking the unweighted mean1 of the z-scores for the lower level indicators or questions.
As this process can be quite laborious, we have already calculated scores for the 16 components and sub-components in our structure, as well as the top-level figures for personal well-being, social well-being and well-being at work. They are included in the dataset and ready to use. If you like, you can also develop your own structure and calculate your own scores based on it. We do warn you though that the exercises that follow are all based on the scores that are already in the dataset, and it will be easier to check your solutions if you use the same scores.
-  Unweighted between components - this means each component is given equal importance.