Abstract

SAGARO DEL CAMPO, Nelsa María  and  ZAMORA MATAMOROS, C. Larisa. Why Use the Implicative Statistical Analysis in Studies of Health Causality?. RCIM [online]. 2019, vol.11, n.1, pp. 88-103.  Epub June 01, 2019. ISSN 1684-1859.

Implicative statistical analysis is a technique of data mining, emerged to solve problems of the Didactic of mathematics, it is based on Artificial Intelligence and Boolean Algebra, to model the quasi-implication between events and variables of a data set. The objective of this essay is to expose the theoretical and practical evidences that demonstrate its utility for the study of causality in health, for which an exhaustive review of the subject was carried out in the bibliographic databases hosted on the internet. A series of reasons are presented that justify the use of this technique in causality studies in medicine, regarding the number of variables, the sample size, the assumptions required for its application and the asymmetric nature of its indices. Also some advantages are identified with respect to traditional statistical techniques such as detection of rare events, which would go unnoticed to measures such as support and trust. Finally, clinical-epidemiological investigations where this analysis has been used are mentioned.

Keywords : Implicative statistical analysis; quasi-implication; similarity; cohesion; entropy; causality in medicine; statistical techniques.

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