I want to run a linear regression based on the data gathered using a questionnaire. Several of the questions have the following form:
How much do you spend on xyz in a month?
a. Less than \$50
b. \$50 to less than \$100
c. \$100 to less than \$200
d. \$200 or more
This is ordinal data, with multiple categories. I am not sure how to code them.
Should I use code them like a Likert scale (though Likert scale data is interval data instead):
0 for a, 1 for b, 2 for c and 3 for d
Or should I use dummy variables like this:
3 dummy variables for options b, c and d, with the respective dummy variable set equal to 1 if the option is chosen and 0 otherwise. All dummy variables are set to 0 if option a is chosen.
In this case I am concerned that all sense of ordinality is lost and I am treating the options just as nominal data. In this case, I think I would not be able to comment on whether the more you spend on xyz, the more you gain weight for example.
Which one should be used? Or should some completely different coding be used?
I seek to use such variables only as regressors, my regressand is a ratio-scale variable.