Title: Forming and coding response categories
Course: UGQuants (SSPS) > Section: Survey Design

Forming and coding response categories

Exclusive and exhaustive categories

Firstly, our chosen categories must be exclusive. In other words we must be able to apply a unique code to each category. If our categories are not exclusive, when we come to assign numbers they will not be able to be applied to distinct categories. Secondly our categories must be exhaustive. In other words, each respondent must belong to one of the categories provided. If our categories are not exhaustive then we will end up with data which cannot be coded. To avoid this potential problem it is often wise to include an ‘Other’ category to accommodate those respondents who do not fit within any of categories provided.

Level of detail

A key consideration when developing a coding scheme is the level of detail to which we should code. This decision will be influenced by a range of factors. Firstly, the selected categories must make sense within the context of the research. For example, the categories we create must be consistent with the theories we are investigating and must be capable of providing the necessary level of detail that we are seeking to report. It is also important to consider whether we wish to compare our research with existing studies. If we wish to make comparisons, it would seem sensible to code to the same level of detail as the relevant studies to allow us to make meaningful comparisons.

Sample size is another important consideration when determining the level of coding detail. If we have achieved or are likely to achieve only a small sample size, then a high level of detail in coding is unlikely to be useful, as the numbers in each category are likely to be too small to undertake meaningful analysis. The issue of resources must also be considered, as a greater level of detail will require a greater investment of time and finance.

Finally, it is important to bear in mind that the more detailed the coding scheme, the greater the chance that coding errors will occur thereby negatively affecting the quality and reliability of our results. Bearing all of these considerations in mind, it is nonetheless advisable to err on the side of caution and opt for greater detail in coding as opposed to lesser detail. When it comes to data analysis, it is always possible to collapse categories should they prove too detailed, however we cannot of course expand upon our categories after completion of data collection should we find that a greater level of detail would have been desirable.