A robust method for regression and correlation analysis of socio-economic indicators

Ordinary least squares regression and ‘product-moment’ correlation are the most commonly used statistical tools for analysing cross-national and other socio-economic indicator data. However, their use depends on assumptions that may not be plausible when applied to such data. Moreover, the use of squared deviations in formulas leads to an exaggerated influence of outliers. In this paper, an alternative methodology based on the ratio of absolute deviations is considered, and a simulation study is presented to evaluate its robustness against outliers and departures from normality. The results show that this methodology is very resistant and has a higher breakdown point than the traditional methods. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.