Hello,
My DV is a binary variable (Yes/No) and I am using a logit/probit regression analysis.
As for my independent variables,there are three I'm primarily interested in. They are all ordinal categorical variables,each of which is of the form:
Strongly Agree
Agree
Indifferent
Disagree
Strongly Disagree
Whats the best way to include those variables in the model?
I could arbitrarily plug some ordered values to each answer (e.g. -10 for "Strongly Disagree", -5 for "Disagree", 0 for "Indifferent", etc).
I could create dummies for each category and put them into the regression.
Or,finally, I could create one dummy for each variable which divides the categories in half and put them into the regression e.g. dummy=1 if ("Str. agree" or "Agree") and dymmy=0 if ("Indif." or "Disagree" or "Str. Disagree")
Which one of the three would you propose I do or, do you have any other alternatives?
Appreciate you time
My DV is a binary variable (Yes/No) and I am using a logit/probit regression analysis.
As for my independent variables,there are three I'm primarily interested in. They are all ordinal categorical variables,each of which is of the form:
Strongly Agree
Agree
Indifferent
Disagree
Strongly Disagree
Whats the best way to include those variables in the model?
I could arbitrarily plug some ordered values to each answer (e.g. -10 for "Strongly Disagree", -5 for "Disagree", 0 for "Indifferent", etc).
I could create dummies for each category and put them into the regression.
Or,finally, I could create one dummy for each variable which divides the categories in half and put them into the regression e.g. dummy=1 if ("Str. agree" or "Agree") and dymmy=0 if ("Indif." or "Disagree" or "Str. Disagree")
Which one of the three would you propose I do or, do you have any other alternatives?
Appreciate you time