  In this paper, we propose the generalized mixed reduced rank regression
method, GMR$^3$ for short. GMR$^3$ is a regression method for a mix of numeric,
binary and ordinal response variables. The predictor variables can be a mix of
binary, nominal, ordinal, and numeric variables. For dealing with the
categorical predictors we use optimal scaling. A majorization-minimization
algorithm is derived for maximum likelihood estimation under a local
independence assumption. We discuss in detail model selection for the
dimensionality or rank, and the selection of predictor variables. We show an
application of GMR$^3$ using the Eurobarometer Surveys data set of 2023.
