A variable is a placeholder for a value that may be represented in a qualitative or quantitative manner. A function is a relationship between multiple variables.
2 major classes of variables:
- Qualitative: represent categories
- Quantitative: represent a measurable quantity
In epidemiology, a variable is understood as a set of attributes.
- Independent variable = exposure, what is manipulated
- Dependent variable = outcome, what is measured
- Refer to the name given to each category, which don’t have a number or rank in a scale
- E.g., surgical sutures, blood groups, occupations, food groups
Ordinal or ranked:
- Refer to the degrees of a measuring scale, which can’t be summed or averaged
- E.g., degrees of burn injury, extent of pitting edema in lower limb, intensity of heart murmur
- There is value in between their values; they are thus infinite.
- E.g., age, height, blood pressure, serum glucose (one can measure a person’s height as 2 m, 2.1 m, 2.2 m, etc.)
- There is no value between them.
- E.g., amount of people (it is not possible to have 1.5 people)
- A continuous data series is divided into categories.
- E.g., religion: People can describe themselves as Christian, Muslim, Jewish, etc.
- Dichotomous, or binary, variables:
- A categorical variable with only 2 values is referred to as a dichotomous or binary variable.
- Example: sick or healthy, alive or deceased, normal or abnormal
- Katz DL, Elmore JG, Wild DMG, Lucan SC. (2014). Describing variation in data. In Katz DL, Elmore JG, Wild DMG, Lucan SC (Eds.), Jekel’s Epidemiology, Biostatistics, Preventive medicine, and Public Health, pp. 105–118.
- Babbie ER. (2009). The Practice of Social Research. 12th edition. Wadsworth Publishing, pp. 14–18.