A Different Approach to Dependence Analysis

This article focuses on a statistical tool for dependence analysis in scientific research. Starting from a recent index of concordance for a multiple linear regression model, a coefficient suitable in catching any monotonic dependence relationship between a dependent variable and an independent variable is derived and discussed. Given its interpretation in terms of monotonic dependence, it is called monotonic dependence coefficient (MDC). It is appropriate to all contexts where the dependent variable is quantitative (continuous or discrete) and the independent variable is at least of ordinal nature; tied data are also allowed. MDC's adequacy is validated through Monte Carlo simulations led by taking into account different scenarios of dependence. Finally, an application to real data is provided to stress MDC's capability of detecting dependence relationships between two variables, even if some pieces of information about original data are lost.