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Where there are several or many values in a nominal or ordered category variable, particularly if the number of cases in the dataset is fewer than 300 or so, or if the frequencies in some of the categories are very small, it may make sense to add together the frequencies in adjacent categories if the variable is ordered, or in a way that ‘makes sense’ if it is nominal. In the alcohol marketing survey, respondents were asked what they felt about alcohol adverts on the whole. Figure 2.4, for example, shows that only 13 out of a total of 920 respondents from the alcohol marketing survey responded ‘I like alcohol adverts a lot’. It seems sensible to add these to the next category, ‘I like alcohol adverts a little’. To keep the value set balanced, the disliking of adverts a little and a lot can also be added together. The 17 who responded ‘Don’t know’ can be treated as missing values (the handling of missing values is considered later in this chapter). The resulting table is shown in Figure 2.5. Note that the Valid Percent is based on the 903 non-missing responses. Box 2.2 shows you how to do this in SPSS.

Figure 2.4 Liking of alcohol adverts

Figure 2.5 Liking of alcohol adverts collapsed to three categories