Title: Independent and dependent variables
Course: UGQuants (SSPS) > Section: Associations Between 2 Variables

Independent and dependent variables

Before we even start to think about causation between two variables we need to think whether it is logically possible that one variable might ‘cause’ another. If we do conclude that is possible, then we think of the variable that might cause or influence the other as the independent variable (also sometimes called the ‘explanatory’ variable) and the variable that might be caused or influenced as the dependent variable (sometimes referred to as the ‘outcome’ variable).

 | For example:
1 | In an association between an individual’s age and voting behaviour, we would say that age is the independent variable and vote the dependent variable. This is because it is illogical to think of someone’s choice of vote ‘causing’ them to grow older or younger, but we might, e.g., say that being older makes people more likely to vote for conservative parties.
2 | In an association between an individual’s sex and their attitudes to homosexuality, we would say that sex is the independent variable and attitudes the dependent variable. This is because it is illogical to think of someone’s attitudes ‘causing’ them to be male or female, but we might, e.g., say that being female makes people more likely to adopt more tolerant attitudes towards homosexuality.
3 | In an association between an individual’s health and the kind of neighbourhood they live in, we would say that neighbourhood is the independent variable and health the dependent variable. This is because although it is not entirely illogical to think of someone’s health as influencing the neighbourhood in which they live, it seems more likely that our immediate environment would influence our health, rather than vice versa.

However, the third example does illustrate that differentiating between and identifying the independent and dependent variable is not always straightforward, especially when we do not have variables like age and sex which seem very unlikely if not impossible to be ‘caused’ by anything else. E.g. in an association between religious denomination and attitudes to moral issues, it seems logically possible both that having certain moral views would influence which religious denomination we choose to identify with, but also that such identification might in turn influence how we view moral issues.

It is also true that the same variable may be thought of logically as the independent or dependent variable depending on the other variable with which it is associated. For example, in an association with educational qualifications, income might logically be the dependent variable but in an association with health it seems much more likely that income would be the independent variable. Even a variable such as age might, in some circumstances, be thought of as the ‘dependent’ variable. For example, in the UK women have a higher life expectancy than men, and older people are therefore somewhat more likely to be women than men. While we would not say that being female ‘caused’ people to be older, we could say that in an association between age and sex in the UK, it is more logical to think of age as the dependent variable. Women (and men) have certain characteristics which mean that, in the UK at least, on average women are more likely to live longer.

It is not strictly necessary to attempt to identify the (likely) independent and dependent variables before exploring the association between variables, but it can be very helpful in adding a logical rigour to analysis.

Finally, note from the examples above that even a confident identification of the independent variable does not amount to a determination of the value of the dependent or outcome variable: we do not say that older people will vote for more conservative parties, only that they might be more likely to do so; women might be more likely to have more tolerant attitudes, but this does not mean that all women will have such attitudes ...