An extended study to measure dependence with grouped-ordinal variables generated by unobserved non-normal variables

In the last decades, the availability of attitudinal surveys generating data of ordinal (discrete) nature has increasingly risen. Such kind of data may be also associated with responses expressed through grouped-continuous scales. This article proposes the use of a recent new dependence measure, called MDC go, suitable to all the scenarios where the independent variable is ordinal and the dependent variable is “grouped” into classes. The promising results of the MDC go coefficient behavior in the case of normally and t-Student distributed variables lead us to extend the investigation to the non-normally distributed variables. A Monte Carlo simulation study is built with the aim of assessing the performance of the MDC go coefficient in comparison with the most common dependence coefficients. Additional evidence on the effectiveness of the MDC go coefficient arises from a real application to data on heart diseases.