In multiple regression, when can ordinal IVs be treated as continuous? I am conducting a multiple regression to see if my IVs can predict my DVs.
I have 10 IVs that are measured on either dichotomous scale (gender, ethnicity, if they have had trauma training), 2 nominal variables (Role and type of service (low, medium, high, low and medium) and then the rest are ordinal variables (age, qualification, length of employment, supervision frequency, and supervision satisfaction).
I have transformed Role and Type of Service IVs into dummy variables.
I am not sure whether I need to transform my ordinal variables into dummy variables, or if these can be entered into the regression model as usual, and be treated as continous?
Any help will be greatly appreciated as I am struggling to find clear answers to this
Thanks in advance

Draw the graphs using each model, overlaid on the same set of axes.  If the categorical graph is close to the continuous, then use the continuous model for simplicity. If there is a gross deviation from linearity, use the categorical model.  The same comment applies to other, nonlinear functions of a continuous variable, such as a quadratic, but start simple, using a linear function. Set all other IVs to a constant like mean or mode in such graphs.
Here is an example., from Chapter 10 of "Understanding Regression Analysis
A Conditional Distribution Approach."

