Title: Values
Course: UGQuants (SSPS) > Section: Introduction to Quantitative Analysis

Values

If we can understand cases as the things that we have data for or about, and variables represent the kind of data we have or want to have for all our cases, then we can say that values are a means of representing the specific data we have for each case with respect to each variable. Or, if you like, they are a means of categorising cases for each variable. Although not entirely unique to quantitative approaches, it is relatively rare to see values discussed and applied in more qualitative research. To help us understand why this might be, it is helpful to compare, e.g., a piece of text from a more qualitative interview designed to allow people to respond to questions in their own terms.

Each case has one and only one unique value for each variable. E.g. for a specific case the value for the variable ‘age in years last birthday’ could be 21 or 22, but not both 21 and 22.While researchers might still want to ‘categorise’ this text as an example or illustration of a particular type of action, belief etc., the same text might be categorised in many different ways even by the same researcher. In contrast, categorisation using values in quantitative research is based on the following principles:

Values must be mutually exclusive – they cannot overlap.
This really just restates the first point, but to give another example, for a variable that records vote at an election where it was only possible to vote for one party (e.g. as in the current system for the UK Westminster parliament), the value for a specific case could be Labour or Conservative, but not both.
For each variable there must be at least 2 values – otherwise it is a constant, not a variable.
E.g. in a survey of pupils at an all-girls school we would not have gender as a variable.
There is no upper limit to the number of values.
This often relates to the level of measurement of the variable. Some types of variable typically have only a small number of possible values, while others might have a potentially infinite number.
For some types of variables in order to simplify data recording and analysis, typically values are recorded as simple numbers that represent a category.
The category itself is sometimes described as the ‘value label’. E.g. for vote at the last election the value ‘2’ might represent the value label ‘Conservative’. In such instances it is the label (i.e. Conservative) rather than the numerical value (i.e. 2) that is important.

These principles raise methodological and practical challenges. The principle of having one unique value for each case and variable leaves no room for qualification or equivocation. This might be a particular problem for more ‘subjective’ variables. When someone’s feelings or attitudes might depend on the particular context then it might seem dubious to speak of them having ‘an’ attitude to a particular issue.

But problems might also arise even with apparently more straightforward and ‘objective’ questions. To use the examples above, if someone lives in a country where birth is not typically recorded or certified and/or birthdays not routinely celebrated then they might genuinely not know whether they are 21 or 22 years old. Perhaps someone voted twice in the election even though they should not have, and thus did vote for Labour and the Conservatives? Issues such as these can be addressed to some extent, e.g., by careful wording of questions and categorisation of responses into values, and by including options such as ‘don’t know’, but in quantitative research we generally want to minimise the number of cases that cannot be clearly categorised and some of the methodological problems are simply limitations of quantitative research that cannot be completely overcome.