A dependence measure flow tree through Monte Carlo simulations

Emanuela Raffinetti () and Pier Alda Ferrari
Additional contact information
Emanuela Raffinetti: University of Milan

Quality & Quantity: International Journal of Methodology, 2021, vol. 55, issue 2, No 5, 467-496

Abstract: Abstract In applied psychological, behavioral and sociological research the majority of data are typically mixed (continuous and discrete) or, if continuous, they violate the normality condition. Given a dependent and an independent variables: (a) both the variables may appear with distinct values (continuous variables); (b) the dependent variable may present distinct values (continuous variable) and the independent variable tied values (discrete variable); (c) the dependent variable may present tied values (discrete variable) and the independent variable distinct values (continuous variable). The dependence relationship between the variables could be assessed through the common correlation coefficients, i.e., the Pearson’s, Spearman’s and Kendall’s coefficients, jointly with a recently revisited monotonic dependence coefficient, called “Monotonic Dependence Coefficient”. But, the choice of the most suitable dependence measure in different scenarios may become problematic. The aim of the paper is to show which dependence measure to use to discover dependence relationships. A flow tree displaying how to find the best dependence measures is proposed by means of a Monte Carlo simulation study. Both Normal and non-Normal distributions producing continuous and discrete data, together with the possibility of transforming discrete data into continuous ones, are considered. Finally, validation of simulation findings on real data is also introduced.

Keywords: Normal and non-normal distributed data; Mixed data; Dependence coefficient; “Continuous-ation” approach (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11135-020-01010-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:qualqt:v:55:y:2021:i:2:d:10.1007_s11135-020-01010-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11135

DOI: 10.1007/s11135-020-01010-9

Access Statistics for this article

Quality & Quantity: International Journal of Methodology is currently edited by Vittorio Capecchi

More articles in Quality & Quantity: International Journal of Methodology from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().