Determination of the effect size of an observed factor based on a multi-variate model for evaluating practical significance of differences between two groups of case-control design

Abstract

Background To determine the effect size of an observed factor for a disease by using consistency in a cohort study (CRC) for evaluating practical significance of differences between two groups of case-control design. Methods A model of multiple pathogenic factors was established by analyzing the number and distribution of observed factors in a study population. The difference in the incidence between two groups (exposed and unexposed) was calculated according to the model as CRC. The relationship of Youden’s index and true and false-positive ratio (TFR) in case-control design were observed with CRC. Results The CRC was able to correctly reflect the number of factors combined in the models, and therefore, indicates that CRC is a reasonable indicator of effect size. Difference scores <0.25 indicate that one of four or more factors plays a role in a disease; scores >0.50 indicate one of two factors plays a role in disease and implies a high intensity level of the factor. TFR could correctly reflect CRC. Accordingly, a factor with an effect size (i.e., CRC) less than 6.0 should not be considered a clinically significant factor, even if the observed difference is statistically significant. Conclusions A CRC over 0.25 OR TFR over 6.0 is suggested as an indicator of a substantial effect size.