Does R automatically convert the categorical variables (predictor) to dummy variables, if the former is changed to factor variables? Or should it be manually converted prior to performing multiple linear regression?
I would remain grateful for your expert comments and thoughts, please.
Pelden Nima R will automatically create dummy variables if the predictor is recognized as a factor. You can check this by using the following code:
is.factor(df$predictor)
If the variable is not recognized as a factor (FALSE), it can be converted to a factor with the following code:
df$predictor
Dummy coding is only the default, you may change it to other contrasts, like effect coding.
Rainer Duesing, thanks a lot but May you explain a bit about effect coding. Have never heard of it.
Effect coding (or sum to zero coding besides other names for it) is another possibility to set up codings. With dummy coding, you compare all levels against a reference level, whereas in effect coding, the "reference" i.e. the intercept is the grand mean value, instead of the mean of the reference group.
Please have a look at the following link, where different coding schemes are explained with examples and alternative names for the same schemes are also presented, very helpful imo:
https://cran.r-project.org/web/packages/faux/vignettes/contrasts.html
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