a) Hierarchical survey data
These are surveys where the data has a hierarchical structure. An example of this might be as follow. You might survey 100 doctors. For each doctor, you might collect data relating to up to 10 patients. For each patient, you might record the dosages and frequency of dose for each drug prescribed. In other words, there are three levels of data – doctors, patients and drugs. In this example, there is a linear hierarchy. Other hierarchies may have different structure and different relationships. MRDCL can handle even the most complex of hierarchical relationships.
b) Repeated questionnaire sections
Some questionnaires have repeated blocks of questions (often called ‘loops’ in data collection software). An example of this would be eating out occasions in a questionnaire where data relating to each ‘eating out occasion’ is recorded. Similarly, a survey might record the television programmes viewed for each hour time band in a diary during a day or over several days. A further example might be where there is a series of identical questions for, say, five products. Although it is possible to treat this data as standard respondent data, MRDCL reduces the amount of work and processes such surveys as a form of hierarchical data – the levels being respondents and occasions or respondents and products discussed.
c) Rotational questionnaire data
A third example of hierarchical data is where there are rotational sections to a questionnaire. A product test is a good example where respondents might, for example, test three products in a random order. Some software solutions resolve this problem by recoding data, but MRDCL has easy-to-use tools that allow you to treat the data as hierarchical data – respondents and products tested.