TITLE:
The Influence Function of the Correlation Indexes in a Two-by-Two Table
AUTHORS:
Giovanni Girone, Fabio Manca, Claudia Marin
KEYWORDS:
Two-by-Two Table, Influence Function, Correlation Indexes, Gross Sensitivity Error, Mean Square Deviation, Asymptotic Variance
JOURNAL NAME:
Applied Mathematics,
Vol.5 No.21,
December
11,
2014
ABSTRACT: In this paper we examine 5 indexes (the two Yule’s indexes, the chi square, the odds ratio and an elementary index) of a two-by-two table, which estimate the correlation coefficient ρ in a bivariate Bernoulli distribution. We will find the compact expression of the influence functions, which allow the quantification of the effect of an infinitesimal contamination of the probability of any pair of attributes of the bivariate random variable distributed according to the above-mentioned model. We prove that the only unbiased index is the chi square. In order to determine the indexes, which are less sensitive to contamination, we obtain the expressions of three synthetic measures of the influence function, which are the maximum contamination (gross sensitivity error), the mean square deviation and the variance. These results, even if don’t allow a definitive assessment of the overall optimum properties of the five indexes, as not all of them are unbiased, nevertheless they allow to appreciating the synthetic entity of the effect of the contaminations in the estimation of the parameter ρ of the bivariate Bernoulli distribution.