By dividing age into categories, we can make comparisons between age groups and start to explore non-linear relationships, noting that we lose information by grouping age into categories while gaining additional information through analyses that categorical variables allow for, such as cross-tabulation and regression with dummy variables.Ģ An Example in SPSS: Satisfaction With Health Services, Health, and Age In the case of age, there are many occasions where this relationship is non-linear. This approach assumes a relationship between the dependent variable and age that is the same across ages. Age in its continuous form ensures a more parsimonious model in regression analyses with only one coefficient for interpretation which can identify significant trends between age and the outcome variable where they exist. Where age is provided in a dataset on a continuous scale, the researcher is provided with the option to include it as a continuous variable or divide it into groups as a categorical variable. While many demographic variables are categorical by nature, for example, religion, race, or nationality, those that are continuous by nature, such as age or income, can be recorded and managed either as continuous or categorical, both at the data collection stage and later in the data processing stage. A researcher might also want to consider whether age acts as a moderator variable such that the relationship between an independent and dependent variable changes according to how old a respondent is.Īge can be considered as a continuous, ratio variable. A researcher might want to understand the direct relationship between age and some outcome, or they might recognise that changes occur with age and thus they must control for age when considering other relationships.

Measurements of age can be of particular interest to social scientists in understanding those changes in behaviours, beliefs, attitudes, and lifestyles that coincide with age. These help to identify representativeness of a particular sample as well as describing participants and providing valuable information to aid analysis. 1 Including Demographic Variable Age in AnalysisĪge is a key demographic variable, frequently recorded in survey data as part of a broader set of demographic variables such as education, income, race, ethnicity, and gender.

Spss code dependent