Contents
Is age a factor variable?
Age is a predictor variable among a few others (gender, weight and height) and my response is the log-odds of a certain disease (binomial glm).
Is age discrete or continuous data?
We could be infinitly accurate and use an infinite number of decimal places, therefore making age continuous. However, in everyday appliances, all values under 6 years and above 5 years are called 5 years old. So we use age usually as a discrete variable.
Is age a nominal or continuous variable?
There are 2 types of numerical variables: ● Continuous variable: A numerical variable that can take values on a continuous scale (e.g. age, weight).
What type of variable is age statistics?
In our medical example, age is an example of a quantitative variable because it can take on multiple numerical values. It also makes sense to think about it in numerical form; that is, a person can be 18 years old or 80 years old. Weight and height are also examples of quantitative variables.
What type of variable is birth month?
1 Expert Answer Since there are exactly 12 possible birth months, it is discrete, and can be categorical. It is qualitative, as it describes an attribute or quality of the subject, namely the birth month.
When to treat a predictor as a continuous variable?
Treating a predictor as a continuous variable implies that a simple linear or polynomial function can adequately describe the relationship between the response and the predictor. When you treat a predictor as a categorical variable, a distinct response value is fit to each level of the variable without regard to the order of the predictor levels.
When to use age as a continuous variable?
So you would probably not want to use age strictly as a continuous variable if your response was alcohol consumption. For a disease: the aging process that might change our probability of getting a disease doesn’t usually happen in sudden shifts, therefore, I would tend to start with a continuous variable.
Should I specify a model predictor as categorical or continuous?
Predictor variables in statistical models can be treated as either continuous or categorical. Usually, this is a very straightforward decision. Categorical predictors, like treatment group, marital status, or highest educational degree should be specified as categorical.
When to use categorical, discrete, and continuous variables?
If you have a discrete variable and you want to include it in a Regression or ANOVA model, you can decide whether to treat it as a continuous predictor (covariate) or categorical predictor (factor). If the discrete variable has many levels, then it may be best to treat it as a continuous variable.