Improving Comparability of Existing Data by Response Conversion

Incomparability of information is the key problem in international comparisons. The usual way to improve comparability is to harmonise data collection efforts. However, harmonisation fails if the data have already been sampled, or if appropriate harmonisation cannot be achieved for whatever reason. This normally leaves no other option than to either make strong unwarranted assumptions about the data, or abandon any comparative work. This article proposes an approach that, under certain circumstances, might provide useful comparative analyses from existing incomparable data. The method, termed Response Conversion (RC), addresses the problem of divergent formulations of survey questions. RC attempts to transform responses obtained on different items (questions) onto a common scale. Where this can be done, comparisons can be made using the common scale. The method consists of two steps. The first step is the construction of a conversion key by means of a statistical model, in our case the polytomous Rasch model. This can only be done if enough overlapping information is available between the different items, but when it is there, RC makes no assumptions about the distribution of the common scores across populations. A linkage map of studies by items provides an important tool t