Understanding the overall research question is not sufficient to make meaningful decisions about the type of output or the most appropriate measures to use. A given research question may be addressed in more than one valid way. It is therefore essential to understand how the specific research question can be answered:
- • Will the analytical approach be primarily descriptive, or will it require more sophisticated statistical techniques (e.g. regression, factor analysis, etc.)?
- • What contextual and other variables are required to answer the research question? If the research question simply involves identifying differences between specific population groups in terms of a small set of key outcomes, the range of relevant co-variates may be relatively limited. However, if the research question is focused on understanding what drives group differences in subjective well-being or on examining the joint distribution between subjective well-being and other dimensions of well-being, the range of co-variates is likely to be significantly broader.
- • What level of accuracy is required to produce meaningful results from the proposed analysis? This will have implications for sample size and sampling strategy. For example, if obtaining precise estimates for small population sub-groups is a priority, then oversampling of these groups may be necessary.
After considering the proposed analytical strategy, it should be possible to articulate how the research questions can be answered in quite specific terms. This will form the basis for evaluating what data needs to be output to support the desired analysis.