What does it mean when an independent variable is continuous?
If a variable can take on any value between its minimum value and its maximum value, it is called a continuous variable; otherwise, it is called a discrete variable.
What does it mean when a variable is continuous?
Continuous variables can take on an unlimited number of values between the lowest and highest points of measurement. Continuous variables include such things as speed and distance. Gender or rank are examples of discrete variables because there are a limited number of mutually exclusive options.
How to handle ordinal categorical variable as a regression?
Let me recommend you also to visit these threads: Associating between nominal and scale or ordinal; Associating between ordinal and scale. They could be helpful despite that they are not about specifially regressions. But these threads are about regressions, particularly logistic: you must look inside: one, two, three, four, five.
Can a continuous variable be used as an independent variable?
It sounds like your independent variable is actually a categorical variable with two levels. Continuous variables don’t have levels like that. You can perform simple regression with one categorical independent variable. However, for simplicity, you can perform a 2-sample t-test and assess the mean difference between your two groups.
What’s the problem with an ordinal independent variable?
The problem with ordinal independent variable is that since, by definition, the true metric intervals between its levels are not known, no appropriate type relationship – apart from umbrella “monotonic” – can be assumed apriori.
Is it better to use a continuous variable in logistic regression?
In logistic regression, as with any flavour of regression, it is fine, indeed usually better, to have continuous predictors. Given a choice between a continuous variable as a predictor and categorising a continuous variable for predictors, the first is usually to be preferred.