[Weibull regression in the analysis of the aging phenomenon of biological systems]

The processing battery represented by standard regressions is totally insufficient for the primary regression analysis of biomedical observation data. Using only this processing system, it is possible to loose a significant amount of information and especially to obtain false conclusions, seeming to be "statistical justified". This conclusion is sustained by the results obtained in this paper on 8 samples. In this paper it was created a calculation algorithm that allows the automatic, simultaneous effectuation of 16 types of regression, obtained by change of variable. This algorithm finally orders these regressions according to the values of correlation coefficient and emphasizes the regression type that mathematically fits the best the observed data. The choice of the optimal regression type depends basically by the fact that the results supplied by that regression corresponds with the biological characteristics of the studied phenomena. In the specific case of optical nerve, in all the 8 samples and sub-samples analyzed, the regression that supplied the higher correlation coefficients was the Weibull model, with exponent variable as a function of time.