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Can ordinal data be used in regression analysis?
Ordinal regression is a member of the family of regression analyses. As a predictive analysis, ordinal regression describes data and explains the relationship between one dependent variable and two or more independent variables.
Can a study have multiple dependent variables?
A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is possible to have experiments in which you have multiple variables. There may be more than one dependent variable and/or independent variable.
How to do multivariate regression of ordinal data?
If an independent variable has e.g. three categories (something like e.g. school-type), then you just recode that variable into three binary ones (0=public school, 1=grammar school, 2=integrated school) and leave one out as the reference category.
Which is an example of Multivariate multiple regression?
Multivariate Multiple Regression is the method of modeling multiple responses, or dependent variables, with a single set of predictor variables. For example, we might want to model both math and reading SAT scores as a function of gender, race, parent income, and so forth.
How to use regression with multiple dependent variables?
Basically, it is a regression framework which relies on the idea of building successive (orthogonal) linear combinations of the variables belonging to each block such that their covariance is maximal. Here we consider that one block X contains explanatory variables, and the other block Y responses variables, as shown below:
Is it possible to do multiple regression in R?
Yes, it is possible. What you’re interested is is called “Multivariate Multiple Regression” or just “Multivariate Regression”. I don’t know what software you are using, but you can do this in R. Here’s a link that provides examples.