Contents
Can linear regression be used for categorical dependent variables?
Categorical variables require special attention in regression analysis because, unlike dichotomous or continuous variables, they cannot by entered into the regression equation just as they are. Instead, they need to be recoded into a series of variables which can then be entered into the regression model.
Can there be multiple dependent variables?
A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is possible to have experiments in which you have multiple variables. There may be more than one dependent variable and/or independent variable.
Is it possible to do regression analysis without a dependent variable?
Therefore, we have to have a way to know this difference i.e. error. Without dependent variable, this is impossible. Therefore, a regression analysis is not possible without dependent variable. If you do not want to use dependent variable, can you elaborate what you are attempting to achieve?
When to normalize dependent and independent variables in regression?
In summary: it is a good habit to check graphically the distributions of all variables, both dependent and independent. If some of them are slightly skewed, keep them as they are. On the other hand, highly skewed variables should be normalized before fitting the model.
How are binary independent variables used in regression?
Binary independent variables are also known as indicator variables and analyst frequently use them in linear regression. Typically, the 1s and 0s of an indicator variable represent the presence or absence of a characteristic.
When to use proportion as dependent variable in regression?
If it’s just a single multiple regression, however, you should look into one of the other methods. A second approach is to treat the proportion as a binary response then run a logistic or probit regression. This will only work if the proportion can be thought of and you have the data for the number of successes and the total number of trials.