SciELO - Scientific Electronic Library Online

 
vol.37 issue1A New Extension of the Exponential Distribution author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Revista Colombiana de Estadística

Print version ISSN 0120-1751

Rev.Colomb.Estad. vol.37 no.1 Bogotá Jan./June 2014

https://doi.org/10.15446/rce.v37n1.44353 

http://dx.doi.org/10.15446/rce.v37n1.44353

On the Performance Evaluation of Different Measures of Association

Evaluación de diferentes medidas de asociación

MUHAMMAD RIAZ1, SHAHZAD MUNIR2, ZAHID ASGHAR3

1King Fahad University of Petroleum and Minerals, Department of Mathematics and Statistics, Dhahran, Saudi Arabia. Professor. Email: riaz76qau@yahoo.com
2Quaid-i-Azam University, Department of Statistics, Islamabad, Pakistan. Professor. Email: farhan.saif@qau.edu.pk
3Quaid-i-Azam University, Department of Statistics, Islamabad, Pakistan. Professor. Email: g.zahid@gmail.com


Abstract

In this article our objective is to evaluate the performance of different measures of associations for hypothesis testing purposes. We have considered different measures of association (including some commonly used) in this study, one of which is parametric and others are non-parametric including three proposed modifications. Performance of these tests are compared under different symmetric, skewed and contaminated probability distributions that include Normal, Cauchy, Uniform, Laplace, Lognormal, Exponential, Weibull, Gamma, t, Chi-square, Half Normal, Mixed Weibull and Mixed Normal. Performances of these tests are measured in terms of power. We have suggested appropriate tests which may perform better under different situations based on their efficiency grading(s). It is expected that researchers will find these results useful in decision making.

Key words: Measures of association, Non-Normality, Non-Parametric methods, Normality, Parametric methods, Power.


Resumen

En este articulo el objetivo es evaluar el desempeño de diferentes medidas de asociación para pruebas de hipótesis. Se consideran diferentes medidas, algunas paramétricas y otras no paramétricas, así como tres modificaciones propuestas por los autores. El desempeño de estas pruebas se evalúa considerando distribuciones simétricas, sesgadas y contaminadas incluyendo la distribución normal, Cauchy, uniforme, Laplace, lognormal, exponencial, Weibull, Gamma, t, Chi-cuadrado, medio normal, Weibull mezclada y normal mezclada. El desempeño se evalúa en términos de la potencia de los tests. Se sugieren tests apropiados que tienen un mejor desempeño bajo diferentes niveles de eficiencia. Se espera que los investigadores encuentren estos resultados útiles en la toma de decisiones.

Palabras clave: medidas de asociación, no normalidad, métodos no paramétricos, métodos paramétricos, potencia.


Texto completo disponible en PDF


References

1. Daniel, W. W. (1990), Applied Nonparametric Statistics, Duxbury Classic Series, New York.         [ Links ]

2. Gauthier, T. D. (2001), 'Detecting the trends using the Spearman's rank correlation coefficient', Environmental Forensics 2, 359-362.         [ Links ]

3. Kendall, M. G. (1938), 'A new measure of rank correlation', Biometrika 5, 81-93.         [ Links ]

4. Mahoney, M. & Magel, R. (1996), 'Estimation of the power of the Kruskal-Wallis test', Biometrical Journal 38, 613-630.         [ Links ]

5. Maturi, T. A. & Elsayigh, A. (2010), 'A comparison of correlation coefficients via a three-step bootstrap approach', Journal of Mathematics Research 2, 3-10.         [ Links ]

6. Mudelsee, M. (2003), 'Estimating Pearson's correlation coefficient with bootstrap confidence interval from serially dependent time series', Mathematical Geology 35, 651-665.         [ Links ]

7. Munir, S., Asghar, Z. & Riaz, M. (2011), 'Performance evaluation of different tests for location parameters', Communications in Statistics-Simulation and Computation 40(6), 839-853.         [ Links ]

8. Spearman, C. (1904), 'The proof and measurement of association between two things', American Journal of Psychology 15, 73-101.         [ Links ]

9. Walker, D. A. (2003), 'JMASM9: converting Kendall's tau for correlational or meta-analytic analyses', Journal of Modern Applied Statistical Methods 2, 525-530.         [ Links ]

10. Yitzhaki, S. (2003), 'Gini mean difference: a superior measure of variability for non normal distribution', Metron-International Journal of Statistics LXI, 285-316.         [ Links ]

11. Zimmerman, D. W. (1994), 'A note on modified rank correlation', Journal of Educational and Behavioral Statistics 19, 357-362.         [ Links ]


[Recibido en agosto de 2012. Aceptado en noviembre de 2013]

Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:

@ARTICLE{RCEv37n1a01,
    AUTHOR  = {Riaz, Muhammad and Munir, Shahzad and Asghar, Zahid},
    TITLE   = {{On the Performance Evaluation of Different Measures of Association}},
    JOURNAL = {Revista Colombiana de Estadística},
    YEAR    = {2014},
    volume  = {37},
    number  = {1},
    pages   = {1-24}
}