Solved – Multiple regression with categorical variables

categorical datamultiple regression

I have a data set with 3 continuous variables and 3 categorical variables. I know that I have to create dummy variables for categorical variables but I am wondering if it is a must to do that for all 3 categorical variables in this case?

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One advantage (out of many) of using R is that it takes care of this problem for you -- no need to assign dummies (just make sure the categorical variables are entered as strings instead of numbers).

Some basics: Multiple regression in R

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Solved – Ordered logit with (too many?) categorical independent variables

Using ordinary least squares (OLS) does not solve the problem you are facing. It only assumes it away. If you are using OLS you are implicitly assuming that the different points on your scale are equally spaced. If you are comfortable with this assumption, push the OLS button and try to convince your audience.

I would tackle the problem differently. You have already mentioned of the solutions. Indeed, it could make sense to recode the control variables and to reduce the number of categories. Sparsely populated categories could be merged to other categories. Use your topical knowledge to merge and redefine categories.

You can also try to recode the dependent variables. Even on a 10 point scale, responses are usually clustered around some modalities. Again, guided by topical knowledge, you could redefine the dependent variable.

This topic is not new on CrossValidated. Under the Likert tag you will find plenty of discussions that may be of interest to you.

Solved – Multiple regression interaction with categorical IV with 3 levels

You can definitely do that. you can introduce your categorical variable as a factorial one. If you have decided to use R programming this following code would be fine:

new_categ<-factor(categ,labels=c(0:2))

Then, you can interact the new categorical variable with other independent ones. You also could find examples centered around your problem in Modern Applied Statistics with S-PLUS by Venables and Ripley. However, if you are not willing to use R, you can still read its examples about regression which are beneficial for figuring out how to solve your problem.

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Solved – Ordered logit with (too many?) categorical independent variables

Solved – Multiple regression interaction with categorical IV with 3 levels

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