Methods for Data Selection in Medical Databases: The Binary Logistic Regression -Relations with the Calculated Risks

The medical studies often require different methods for parameters selection, as a second step of processing, after the database’s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn’t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true. Keywords—Databases, risk factors, binary logistic regression, hierarchy.