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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.
Can a logistic regression be both discrete and continuous?
Just like in any ordinary linear regression, the covariates may be both discrete and continuous. The basic principle for logistic regression is the same whether covariates are discrete or continuous, but some adjustments are necessary for goodness-of-fit testing.
Which is an example of an ordinal categorical variable?
A common example is to provide information about an individual’s Body Mass Index by stating whether the individual is underweight, normal, overweight, or obese. This categorized BMI is an example of an ordinal categorical variable.
How are ordinal variables used in biostatistics?
However, ordinal variables are still categorical and do not provide precise measurements. Differences are not precisely meaningful, for example, if one student scores an A and another a B on an assignment, we cannot say precisely the difference in their scores, only that an A is larger than a B.
How can I perform a factor analysis with categorical ( or )?
Note that variables used with polychoric may be binary (0/1), ordinal, or continuous, but cannot be nominal (unordered categories). Also note that the correlations in the matrix produced by the polychoric command are not all polychoric correlations.
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.
Which is an example of a categorical predictor?
For example, categorical predictors include gender, material type, and payment method. Discrete variable. Discrete variables are numeric variables that have a countable number of values between any two values. A discrete variable is always numeric.